Introduction
Lung cancer accounts for the highest number of
cancer-related deaths worldwide, resulting in ~1.8 million deaths
(18.7% of all cancer mortalities) (1). Non-small cell lung cancer (NSCLC),
which comprises ~85% of all lung cancer cases, is the most common
subtype (2). Conventional
treatments, including chemotherapy, surgery and radiotherapy, are
widely used for lung cancer (3).
However, these approaches often have limited effectiveness,
particularly for advanced NSCLC.
Targeted therapy and immunotherapy have gained
significant attention as promising alternatives in pre-clinical and
clinical studies over recent years (4) and selectively target cancer cells
while minimizing damage to normal cells (5). Immunotherapy, in particular, enhances
the immune system's ability to recognize and eliminate cancer
cells, overcoming mechanisms of immune evasion, such as through the
use of immune checkpoint inhibitors (6). These approaches mainly focus on
precise binding to specific proteins on cancer cells, particularly
those signaling pathways involved in the pathogenesis of NSCLC
(7), making the selection of
appropriate proteins crucial. Previous studies have identified
multiple tumor-associated antigens (TAAs) that are upregulated in
patients with NSCLC, including mesothelin, human epidermal growth
factor receptor-2, epidermal growth factor receptor (EGFR),
mesenchymal-epithelial transition factor and folate receptor α.
Trophoblast cell surface antigen-2 (TROP-2), encoded
from tumor-associated calcium signal transducer 2, is a
transmembrane glycoprotein that is primarily involved in cell
signaling, adhesion, and proliferation (8). In normal tissues, TROP-2 is expressed
at low levels and plays a role in tissue regeneration and embryonic
development (8). Notably, a recent
review noted that TROP-2 is overexpressed in NSCLC, where it
promotes tumor growth, invasion and metastasis by enhancing cell
proliferation and survival (8).
According to this review, high TROP-2 expression is associated with
poor prognosis in patients with NSCLC (8). Additionally, a recent review
highlighted transmembrane glycoprotein mucin-1 (MUC-1) as another
tumor-associated antigen (TAA) in NSCLC (9). It normally covers the epithelial cells
of the mucous membrane, providing lubrication and protection
(9). However, aberrant expression
of MUC-1 is involved in cancer development, invasion and metastasis
(9). Upregulation of MUC-1 has been
reported to be highly associated with the progression of different
epithelial cancer types, including NSCLC (9). Given their individual roles in tumor
progression, TROP-2 and MUC-1 represent promising targets for
immunotherapeutic approaches (8,9).
Recent evidence suggests that MUC-1 and TROP-2 may be co-regulated
through galectin-3-MUC-1-mediated Specific protein 1 (Sp1)
recruitment and leads to TROP-2 transcription (10). This provides a biological rationale
for evaluating both TAAs as prognostic markers. To date, to the
best of the authors' knowledge, no systematic review or
meta-analysis has comprehensively evaluated the prognostic
importance of TROP-2 and MUC-1 expression for their potential as
immunotherapy targets in NSCLC.
The present systematic review and meta-analysis
analyzed available evidence on the expression levels of TROP-2 and
MUC-1 in NSCLC patients to evaluate their diagnostic, prognostic
and therapeutic relevance. Immunohistochemical studies have
revealed that both antigens are highly expressed in NSCLC tissues
and are associated with reduced overall survival (OS) and
disease-free survival (DFS). These findings are consistent with
prior experimental and clinical studies suggesting that TROP-2 and
MUC-1 contribute to tumor progression through mechanisms such as
cancer cell invasion, epithelial-mesenchymal transition (EMT), and
metastasis. Collectively, this meta-analysis supported the
prognostic value of TROP-2 and MUC-1, individually and in
combination, by exploratory pooled analysis in NSCLC, providing
clinical support for the development of TROP-2 and MUC-1-directed
therapeutic strategies to improve patient outcomes.
Materials and methods
Search strategy
The present study was conducted in the PubMed
(pubmed.gov), Scopus (scopus.com) and
EMBASE (embase.com) electronic bibliographic databases.
To focus on contemporary treatment contexts and recent diagnostic
methodologies, the search was restricted to studies published
within 5 years of data collection (January 2019-December 2024). The
MeSH term ‘NSCLC’ was combined with its synonymic terms (non-small
cell lung carcinoma, NSCLC, Lung carcinoma (s), Lung cancer (s),
Lung neoplasm (s), Lung tumo (ur, urs, s). The MeSH term ‘TROP-2 or
MUC-1’ was also combined with their synonymous terms
(Tumor-associated calcium signal transducer 2, TROP-2,
Transmembrane glycoprotein Mucin 1, Mucin 1, MUC-1, CA 15.3
Antigen, Epithelial membrane antigen, EMA, Episialin, CD227). The
present review was registered in PROSPERO ID: CRD42024597178.
Population, Intervention, Comparison, and Outcome (PICO) details
were Population: Patients diagnosed with NSCLC who exhibited levels
of TROP-2 or MUC-1 expression with available clinicopathological
parameters, OS or DFS, and values of hazard ratio (HR) with 95%
confidence interval (CI). Intervention: The high levels of TROP-2
and MUC-1 expression in NSCLC. Comparator: A group of NSCLC
patients with low levels of TROP-2 and MUC-1. Outcome was OS and
DFS.
Inclusion and exclusion criteria
To be eligible for inclusion in the present study,
the research must not be a review article, must involve only human
subjects, be written in English, have full-text availability and be
published within 5 years of the date of data collection.
Study selection
Two reviewers (PN and JL) independently evaluated
all the studies retrieved using Covidence software (https://www.covidence.org) to ensure transparency and
reproducibility in the selection process. Titles and abstracts were
initially screened to exclude irrelevant articles, reviews, case
reports and non-English publications. Full-text articles that met
the inclusion criteria were then assessed for eligibility.
Discrepancies between the reviewers were resolved through
discussion and, when necessary, a third reviewer was consulted to
reach consensus. The inclusion criteria focused on studies
reporting TROP-2 and/or MUC-1 expression in NSCLC tissues and
corresponding clinicopathological or survival data. The present
study selection process was documented and summarized using a
Reporting Items for Systematic Reviews and Meta-Analyses 2020
Version (PRISMA) flow diagram (https://www.prisma-statement.org).
Data extraction and quality
assessment
Data extraction and quality assessment were
independently reviewed by four reviewers (PN, JL, SL and CT). Data
were extracted from each study on the first author's name, year of
publication, total number of patients, the TROP-2 or MUC-1
expression levels in NSCLC patient tissues/serum/plasma/RNA
sequencing data and progression of NSCLC patients using parameters
such as median OS, DFS, progression free survival (PFS) and HR. The
included studies used different criteria to define TROP-2 or MUC-1
positivity. To standardize the analysis, expression data were split
into high vs. low groups according to the definitions provided by
the original authors. The prognostic outcomes were extracted and
systematically analyzed. The analysis relied primarily on the HR
and CI reported by the original study authors, as these values had
already been calculated using cut-off values that were pre-defined
and specific to each individual study.
Risk of bias in individual
studies
The results of the articles with the assessed risk
of bias were selected using the revised Cochrane Risk-of-Bias Tool
for Randomized Trials 2019 Version (ROB2 Tool) (https://www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2)
for randomized controlled trial studies (Table I) and the Newcastle-Ottawa Scale
(NOS) (https://www.ohri.ca/programs/clinical_epidemiology/oxford.asp)
for cohort studies (Table II).
Publication bias was not formally assessed because <10 studies
were included in the pooled analysis, which renders measures such
as the Egger's or Begg's statistical tests unreliable.
 | Table ICochrane risk-of-bias tool for
randomized trials (ROB2 Tool). |
Table I
Cochrane risk-of-bias tool for
randomized trials (ROB2 Tool).
| | Domain | |
|---|
| First author/s,
year | Bias arising from
the randomization process | Bias due to
deviations from intended interventions | Bias due to missing
outcome data | Bias in the
measurement of the outcome | Bias in the
selection of the report result | Overall RoB
Judgement | (Refs.) |
|---|
| Bessede et
al, 2024 | Low | Low | Low | Low | Low | Low | (11) |
| Table IINOS for assessing the quality of
cohort studies. |
Table II
NOS for assessing the quality of
cohort studies.
| | Selection | Comparability | Outcome | | | |
|---|
| First author/s,
year | S1 | S2 | S3 | S4 | C1 | O1 | O2 | O3 | Total Quality
Score | Grading quality of
the studies | (Refs.) |
|---|
| Sun et al,
2021 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 | Good | (12) |
| Mito et al,
2020 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 | Good | (13) |
| Tu et al,
2022 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 | Good | (14) |
| Haratake et
al, 2024 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | Good | (15) |
| Buyuk et al,
2023 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 | Good | (16) |
| Xie et al,
2021 | 1 | 1 | 1 | 1 | 2 | 1 | 0 | 1 | 8 | Good | (17) |
| Jiang et al,
2020 | 1 | 1 | 1 | 1 | 2 | 1 | 0 | 0 | 7 | Good | (18) |
| Bes-Scartezini
et al, 2022 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 | Good | (19) |
| Kato et al,
2021 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 | Good | (20) |
| Mohamadnia, et
al, 2022 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 4 | Fair | (21) |
| Pan et al,
2019 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 5 | Fair | (22) |
Statistical methods
As no individual study simultaneously assessed the
expression of TROP-2 and MUC-1 in the same patient cohort, the
exploratory analysis was performed by pooling HRs derived from
separate studies that investigated each biomarker independently.
This approach aimed to provide an exploratory estimate of their
overall prognostic relevance rather than a true patient-level
dual-marker effect.
Pooled HRs and their 95% CIs were used to determine
the association between either TROP-2 or MUC-1 expression and OS.
The statistical analyses were performed using Review Manager
(RevMan) version 5.4. Rationale for Exploratory pooled analysis
(https://www.cochrane.org/products-and-services/review-writing-software):
Given that both TROP-2 and MUC-1 are highly expressed TAAs in NSCLC
and are mechanistically involved in promoting cancer cell invasion
and metastasis, their combined expression was analyzed to
investigate their overall prognostic relevance as independent
biomarkers of OS. Heterogeneity among studies was assessed using
the χ2 test and I2. A P-value of <0.1 or
an I2 statistic of >50% was indicative of significant
heterogeneity between studies; in these cases, a random-effects
model was used.
In the presence of low statistical heterogeneity
(I²<50%), a fixed-effect model was applied for the primary
analysis. However, given the limited number of studies and
limitations of the I² statistic in this context, an additional
sensitivity analysis using a random-effects model was performed to
assess the robustness of the pooled estimates. P<0.05 was
considered to indicate a statistically significant difference.
Sensitivity analysis was also performed using a leave-one-out
approach to evaluate the influence of each study on the overall
pooled HRs. The original HRs (95% CIs) were mathematically inverted
by taking their reciprocals (1/HR) to ensure consistency in
interpretation.
Results
Study selection and
characteristics
A comprehensive systematic literature search across
three databases, including PubMed, Scopus, and EMBASE, identified a
total of 1,297 studies that were imported into Covidence to be
screened. After removing 327 duplicate records, 970 unique
citations were screened for title and abstract. This initial
screening excluded 912 records that did not meet the inclusion
criteria or were deemed irrelevant to the research question. The
remaining 58 full-text articles were retrieved and assessed for
eligibility. Following the full-text review, 46 studies were
excluded for the following reasons: Seven studies did not involve
human subjects, 15 studies had no full-text availability, one was
identified as a review article and 23 studies were irrelevant to
the specific research objectives. Ultimately, 12 studies met all
inclusion criteria and were included in the present systematic
review and meta-analysis. The present study selection process was
conducted independently by two reviewers (PN and JL) and documented
according to the PRISMA guidelines (Fig. 1). All included studies provided data
on TROP-2 and/or MUC-1 expression in NSCLC patients with
corresponding clinicopathological parameters and survival
outcomes.
TROP-2 and prognostic value in NSCLC
patients
Among the 12 studies, only three investigated the
effect of TROP-2 on the progression of NSCLC (Table III). Bessede et al
(11) conducted a randomized
controlled trial involving 405 NSCLC patients to examine the
association between TROP-2 expression and treatment outcomes with
the atezolizumab anti-programmed cell death ligand 1 (PD-L1) drug.
This study demonstrated that elevated TROP-2 expression was
correlated with a poor prognosis. The patients were classified as
high TROP-2 or low TROP-2 based on an optimized threshold obtained
using maximally selected rank statistics from the maxstat R package
(https://CRAN.R-project.org/package=maxstat). The
result showed that patients with high TROP-2 expression had a
median OS of 12.6 months compared with 16.3 months in those with
low expression. The HR of OS of the low TROP-2 expression group of
patients was 0.73 (95% CI: 0.57-0.92) with a statistical
significance (P=0.007) and in PFS it was 0.69 (95% CI: 0.56-0.84)
with a statistical significance (P<0.001; Table III).
| Table IIISummary of TROP-2 expression and
clinical outcomes in NSCLC patients. |
Table III
Summary of TROP-2 expression and
clinical outcomes in NSCLC patients.
| First author/s,
year | Population | Treatment | Expression (%) | Median OS (negative
vs. positive) | HR of OS (95%
CI) | P-value | HR of PFS (95%
CI) | P-value | Conclusion | (Refs.) |
|---|
| Bessede et
al, 2024 | Randomized Phase II
POPLAR and Phase III OAK trials (n=405) | Atezolizumab
(IV/1,200 mg/q 3 weeks) | N/A | 16.3 vs. 12.6 | 1.37a (1.09-1.75) | 0.007 | 1.45a (1.19-1.79) | <0.001 | High TROP-2 level
was associated with worse outcomes in NSCLC patients treated with
atezolizumab. | (11) |
| Sun et al,
2021 | NSCLC patients
(n=164) | Gefitinib | 51.22% | Log-rank
χ2=5.817 | N/A | 0.016 | N/A | N/A | High TROP-2 level
in NSCLC patients with EGFR mutations was associated with earlier
drug resistance and poor OS during gefitinib treatment. | (12) |
| Mito et al,
2020 | Retrospective study
(n=331; ADC=228 and SCC=103) | N/A | 38% in ADC; 35% in
SCC | N/A | ADC 2.05
(1.06-4.00) | 0.0326 | ADC 1.40
(0.82-2.36) | 0.2175 | Increased TROP-2
level was markedly associated with a poor clinical course in ADC
patients, but not in those with SCC. | (13) |
Another study analyzed TROP-2 expression in 164
NSCLC patients by immunohistochemical staining and reported that
51.22% (84/164) exhibited high TROP-2 expressions, defined by a
semi-quantitative histology score (H-score) of ≥130(12). Moreover, the increase in TROP-2
expression was correlated with poor disease prognosis in patients
treated with gefitinib. The log-rank χ2 test for median
OS between patients with high and low TROP-2 expression was 5.817,
indicating statistical significance (P=0.016; Table III).
Mito et al (13) conducted a retrospective study in 331
NSCLC patients, including 228 with lung adenocarcinoma (ADC) and
103 with lung squamous cell carcinoma (SCC). The expression of
TROP-2 was evaluated by immunohistochemical staining and used
intensity (0-3) and proportion (0-3) scores to generate a summary
score. The median summary scores were 4.5 in ADC and 5 in SCC.
Cases with a total score >4.5 were classified into the high
TROP2 expression group. The study demonstrated that high TROP-2
expression was found in 38% of total ADC samples and 35% of total
SCC samples. Furthermore, the elevated TROP-2 level was markedly
correlated with abnormal p53 nuclear expression and poor OS.
Univariable analysis in ADC revealed a HR of OS was 2.05 (95% CI:
1.06-4.00) for high vs. low TROP-2 expression, with a statistical
significance (P=0.0326), and HR of PFS was 1.40 (95% CI: 0.82-2.36)
with no statistical significance (P=0.2175; Table III).
MUC-1 and prognostic value in NSCLC
patients
A total of nine studies investigated MUC-1
expression levels in NSCLC patients (Table IV). Of them, two studies analyzed
data from genome databases and classified patients into high and
low MUC-1 groups (14,15). Analysis of 136 NSCLC patients from
The Cancer Genome Atlas had high MUC-1 mRNA expression (15). Its high expression was associated
with poor clinical outcomes following osimertinib treatment
(15). Tu et al (14) showed that MUC-1 mRNA expression
increased in 50.03% of 1,925 NSCLC patients from the genome
database. Prolonged OS was positively associated with MUC-1
expression, with a HR (95% CI) of 0.67 (0.59-0.76) and with
statistical significance (P=4.6x10-10); and high MUC-1
was markedly associated with worse DFS, with an HR of 1.5
(P=0.001), indicating a 50% higher risk of recurrence or
progression compared with low MUC-1 expression.
| Table IVSummary of MUC-1 expression and
clinical outcomes in NSCLC patients. |
Table IV
Summary of MUC-1 expression and
clinical outcomes in NSCLC patients.
| First author/s,
year | Population | Treatment | Expression (%) | Median OS (neg vs.
pos) | HR of OS (95%
CI) | P-value | HR of DFS (95%
CI) | P-value | Conclusion | (Refs.) |
|---|
| Tu et al,
2022 | KM plotter from
genome database (n=1925) | N/A | 50.03% | Low<high | 0.67
(0.59-0.76) | 4.6E-10 | 1.5 (n=962) | 0.001 | Increased MUC-1
mRNA expression is associated with favorable OS but worse DFS. | (14) |
| Haratake et
al, 2024 | The Cancer Genome
Atlas (n=136) | Osimertinib | 60.30% | 22.4 vs.
16.6a 66.4 vs.
6.9b | 2.49
(0.70-8.87) | 0.1 | 4.17
(1.60-10.82) | 0.0015 | High MUC-1
expression in EGFR-mutant NSCLCs was associated with poor clinical
outcomes. | (15) |
| Buyuk et al,
2023 | Retrospective
cohort study ADC (n=99) | N/A | 55.56% | N/A | N/A | N/A | N/A | N/A | Depolarized MUC-1
expression was associated with lymphatic invasion, more advanced
tumor stage, and larger tumors. | (16) |
| Xie et al,
2021 | Prospective cohort
ADC (n=176) | Radical surgery and
systematic nodal dissection | 42.00% | N/A | N/A | N/A | N/A | N/A | MUC-1 expression in
patients was related to differentiation and TNM stage. | (17) |
| Jiang et al,
2020 | NSCLC patients
(n=131) | N/A | 61.83% | N/A | N/A | N/A | N/A | N/A | MUC-1-C expression
was highly expressed in NSCLC especially in female, non-smoker
patients with advanced-stage ADC. | (18) |
| Bes-Scartezini
et al, 2022 | Retrospective
cohort study non-SCC (n=112) | N/A | 50.60% | 18.57 vs.
13.44 | 1.87
(1.13-3.10) | 0.016 | N/A | N/A | High pre-treatment
levels of MUC-1 were correlated with decreased survival in
non-SCC. | (19) |
| Kato et al,
2021 | Retrospective
cohort study ADC (n=175) | N/A | High: 25.14% | 5-year OS rate Low
to Moderate: 87.9% High: 69.3% | 2.797
(1.579-4.956) | <0.001 | N/A | N/A | Overexpression of
MUC-1-Tn was strongly associated with EMT potential and poor
survival in patients with ADC. | (20) |
| Mohamadnia, et
al, 2022 | NSCLC patients
(n=30) | N/A | 63.3% | N/A | N/A | N/A | N/A | N/A | NSCLC patients and
healthy controls show significant difference in marker
positivity. | (21) |
| Pan et al,
2019 | NSCLC patients
(n=27) | N/A exosomes
patients= 1.55±0.16 | Mean | diagnostic value
AUC= 0.685 (0.526-0.818) | N/A | N/A | N/A | N/A | Exosomal MUC-1
might be valuable in distinguishing NSCLC patients from healthy
controls. | (22) |
Notably, three studies investigated the level of the
MUC-1 protein in lung tissues and its relation to
clinicopathological properties (16-18).
A retrospective study conducted by Buyuk et al (16) indicated that 55.56% of ADC samples
had a high immunoreactive score, and the increase of depolarized
MUC-1 (characterized by expression on the entire cell surface or
throughout the cytoplasm) was associated with lymphatic invasion,
more advanced tumor stage and larger tumor size. Similarly, Xie
et al (17) analyzed
formalin-fixed paraffin-embedded (FFPE) lung tissue samples from
176 ADC patients at different stages and showed that 42% of samples
exhibited high MUC-1 and a statistically significant correlation
between MUC-1 expression levels and tumor stage. Jiang et al
(18) studied 131 NSCLC patients
using immunohistochemistry staining and found that 61.83% had high
MUC-1 levels, particularly elevated in female and non-smoker
patients with advanced ADC.
Two studies conducted retrospective cohort studies
analyzing the correlation between MUC-1 level and clinical outcomes
(19,20). Bes-Scartezini and Saad Junior
(19) found that 50.60% of 112
NSCLC patients had high soluble MUC-1 levels (>25-30 UI/ml),
which was associated with decreased overall survival (OS). The
median OS for patients with low MUC-1 was 18.57 months, and 13.44
months for those with high MUC-1. The HR between these groups was
1.87 (95% CI: 1.13-3.10) with statistical significance (P=0.016).
Kato et al (20) examined
lung tissues from FFPE samples obtained via core needle biopsy and
immunohistochemistry staining of MUC-1-Tn, which is an antigen that
may be a novel epitope recognized by MUC-1-Tn epitope-defined
antibody (MUC-1-Tn ED Ab). The authors found that 25.14% of samples
had high MUC-1-Tn expression (>0.14), and MUC-1-Tn
overexpression was associated with poor OS. The five-year OS rate
was 87.9% in the low-to-moderate expression group and 69.3% in the
high-expression group. The HR was 2.797 (95% CI: 1.579-4.956) with
statistical significance (P<0.001).
Two studies investigated MUC-1 in the blood of NSCLC
patients (21,22). Mohamadnia et al (21) compared MUC-1 levels in blood samples
between 30 NSCLC patients and 30 healthy subjects. High MUC-1 was
observed in 63.3% of NSCLC patients and 17% of healthy subjects,
showing a 2.64-fold increase in NSCLC patients with statistical
significance (P=0.031). Pan et al (22) measured MUC-1 exosomes in plasma
using electrochemiluminescence immunoassay analysis in 27 NSCLC
patients and 16 healthy subjects. The mean exosome levels were
1.55±0.16 in NSCLC patients and 1.05±0.06 in healthy subjects. The
study concluded that exosomal MUC-1 might be valuable in
distinguishing NSCLC patients from healthy controls, with a
diagnostic value Area under the curve (AUC) (95% CI)=0.685
(0.526-0.818) and statistical significance (P=0.0234).
Meta-analysis of TROP-2 and MUC-1
expression and OS
Forest plot analysis demonstrated distinct
prognostic patterns for TROP-2 and MUC-1 in NSCLC patients
(Fig. 2). Elevated TROP-2
expression was markedly associated with poor OS, with an HR of 1.43
(95% CI: 1.15-1.79; P=0.002) based on two studies comprising 736
patients (Fig. 2A). Heterogeneity
among TROP-2 studies was low (I²=20%; χ2=1.26; P=0.26),
indicating consistency across studies. The two included studies
showed concordant directional effects, which, after reciprocal
calculation, Bessede et al (11) (2024; n=405) reported HR of 1.37 (95%
CI: 1.08-1.74) and Mito et al (13) (2020; n=331) reported HR of 2.05 (95%
CI: 1.06-3.98).
Similarly, increased MUC-1 expression demonstrated a
significant correlation with worse OS (HR=2.25; 95% CI: 1.57-3.23;
P<0.0001) across three studies with 423 patients (Fig. 2B). Low heterogeneity was observed,
indicating consistency between the included studies (I²=0%;
χ²=1.10; P=0.58). Three included studies showed consistent
outcomes, with Bes-Scartezini and Saad Junior (19) (2022; n=112) reporting HR of 1.87
(95% CI: 1.13-3.10), Haratake et al (15) (2024; n=136) reporting HR of 2.49
(95% CI: 0.70-8.86) and Kato et al (20) (2021; n=175) reporting HR of 2.80
(95% CI: 1.58-4.96).
A sensitivity analysis was performed using a
random-effects model to assess the robustness of the pooled
estimates given the limited number of included studies. As shown in
Table V, the pooled HRs from the
random-effects model were comparable to those derived from the
fixed-effects model. The direction and statistical significance of
the associations remained unchanged for TROP-2, MUC-1 and the
exploratory pooled analysis, indicating that the results were
generally robust despite the small number of studies. When both
markers were evaluated together, high expression of TROP-2 and
MUC-1 was markedly associated with short OS (HR 1.62; 95% CI
1.34-1.96; P<0.00001; Fig. 2C).
Heterogeneity remained low (I²=40%; χ²=6.67; P=0.15).
| Table VSensitivity analysis comparing
fixed-effect and random-effects models. |
Table V
Sensitivity analysis comparing
fixed-effect and random-effects models.
| | Fixed-effect
model | Random-effect
model |
|---|
| Study | HR | 95% CI | HR | 95% CI |
|---|
| TROP-2
expression | 1.43 | (1.15, 1.79) | 1.48 | (1.08, 2.02) |
| MUC-1
expression | 2.25 | (1.57, 3.23) | 2.25 | (1.57, 3.23) |
| Exploratory pooled
analysis of TROP-2 and MUC-1 | 1.62 | (1.34, 1.96) | 1.83 | (1.35, 2.48) |
Discussion
The present study conducted a systematic review and
meta-analysis of 12 eligible studies carefully selected from 1,297
publications, comprising three studies on TROP-2 and nine on MUC-1.
The two groups concluded that elevated TROP-2 and MUC-1 levels were
observed in NSCLC patients. Analysis of the correlation between
TROP-2 or MUC-1 expression levels and clinical outcomes revealed
that high expression levels were markedly associated with poor
clinical outcomes and short survival. Notably, the exploratory
pooled analysis of TROP-2 and MUC-1 expression suggests a potential
association with an unfavorable prognosis, although this should not
be interpreted as evidence of a true dual-biomarker effect. These
findings underscore the prognostic value of TROP-2 and MUC-1 and
their potential as therapeutic targets for personalized treatment
strategies in NSCLC.
The NSCLC patients with high TROP-2 expression were
markedly associated with reduced survival and aggressive tumor
behaviors (11-13).
Several mechanisms may underlie these associations (Fig. 3). TROP-2 overexpression may induce
T-cell apoptosis due to its immunoregulatory role, although the
precise mechanism remains unclear (23) (Fig.
3E). High TROP-2 was markedly correlated with p53 mutations,
which then promoted the production of transforming growth
factor-beta (TGF-β) (24,25). This pathway induces cancer
metastasis by inhibiting Smads/p63 signaling, which specifically
suppresses epithelial differentiation and enhances the EMT, a
crucial step in metastasis via the reduction of E-cadherin and the
increase of mesenchymal markers such as vimentin and N-cadherin
(24,25) (Fig.
3A) that facilitates cytoskeletal reorganization, cell
detachment and invasive behavior. The loss of p63 also allows tumor
cells to escape normal growth control and acquire stem cell-like
properties (24). Additionally,
TROP-2 contributed to resistance against gefitinib by facilitating
NSCLC cell migration and proliferation through the insulin-like
growth factor 2 (IGF2)/insulin-like growth factor receptor
(IGF1R)/Akt signaling axis, which is crucial for drug resistance
and tumor microenvironment (TME) remodeling in NSCLC (12) (Fig.
3D).
 | Figure 3Proposed schematic mechanisms by
which TROP-2 and MUC-1 overexpression contribute to poor NSCLC
patient clinical outcomes through promoting immune evasion,
metastasis, and drug resistance. TROP-2 induces T-cell apoptosis,
enhances TGF-β-driven metastatic signaling linked to p53
alterations, and activates the IGF2/IGF1R/Akt axis to support
proliferation, migration, and gefitinib resistance. MUC-1,
particularly MUC-1-C, upregulates PD-L1 via NF-κB and c-MYC,
suppresses immunity through Tn-MGL interactions, and modulates
apoptosis through BAX. It also cooperates with EGFR and other RTKs
to drive EMT, stemness, and resistance to osimertinib, while
galectin-3 further amplifies TROP-2 expression to reinforce
oncogenic signaling. (A) High TROP-2 expression is linked to p53
mutations, increasing TGF-β production and suppressing Smads/p63
signaling to promote metastasis. (B) The Tn antigen on MUC-1 binds
MGL on immune cells, driving immunosuppression and metastasis. (C)
MUC-1 cooperates with EGFR and other RTKs to activate signaling
that promotes EMT, stemness, and resistance to osimertinib. (D)
TROP-2 enhances migration, proliferation, and gefitinib resistance
via the IGF2/IGF1R/Akt pathway. (E) TROP-2 induces T-cell apoptosis
through immunoregulatory activity. (F) Galectin-3 binding to MUC-1
recruits Sp1 to the TROP-2 promoter, increasing TROP-2 expression
and reinforcing oncogenic signaling. (G) MUC-1 regulates apoptosis
through interaction with BAX, and (H) MUC-1-C activates PD-L1
transcription through NF-κB or c-MYC, leading to T-cell
suppression. Figure was created with BioRender.com. Akt, protein kinase B; BAX,
BCL2-associated X protein; Bcl-2, B-cell lymphoma 2; Bcl-xL, B-cell
lymphoma-extra large; c-MYC, cellular myelocytomatosis; EGFR,
epidermal growth factor receptor; EMT, epithelial-mesenchymal
transition; IGF1R, insulin-like growth factor receptor; IGF2,
insulin-like growth factor 2; MUC-1, mucin-1; mp53, mutant p53;
NF-κB, nuclear factor kappa B; NSCLC, non-small cell lung cancer;
p63, tumor protein 63; PD-1, programmed cell death protein 1;
PD-L1, programmed death-ligand 1; RTKs, receptor tyrosine kinases;
SMAD2, mothers against decapentaplegic homolog 2; Sp1, specificity
protein 1; TGF-β, transforming growth factor-beta; TGF-R,
transforming growth factor receptor; TKI, tyrosine kinase
inhibitor; Tn-MGL, Tn antigen-macrophage galactose-type C-type
lectin; TROP-2, trophoblast cell surface antigen-2. |
For MUC-1, a two-sample binomial test comparing its
positivity in NSCLC patients and healthy subjects revealed a
significant difference between the two groups. The average initial
copy number of this marker in patients was 2.64 times higher than
in healthy subjects (21).
Additionally, another study suggested that plasma exosomal MUC-1
has potential as a diagnostic marker for NSCLC, as its levels were
markedly elevated in NSCLC patients compared with healthy controls
(22). High MUC-1 levels were
associated with cancer progression, poor clinical outcomes, low OS
and increased resistance to therapy. However, increased MUC-1 mRNA
expression was associated with favorable OS, but shorter DFS,
indicating possible context-dependent effects (14).
MUC-1 can regulate the progression of cancer in
several ways (Fig. 3). The
C-terminal of MUC-1 (MUC-1-C) interacts with NF-κBp65 or C-MYC on
the PD-L1 promoter, inducing PD-L1 activation, leading to T-cell
exhaustion and immune evasion (26,27).
These lead to T-cell suppression, contributing to worse clinical
outcomes and greater resistance to immunotherapy (26,27)
(Fig. 3H). This effect, which has
been demonstrated in studies of treatment with evodiamine,
specifically targets MUC-1-C and disrupts its interaction with
NF-κB and C-MYC, leading to downregulation of the MUC-1-C/PD-L1
axis and resulting in improved clinical outcomes (26). Moreover, binding of the Tn antigen
on MUC-1 to macrophage galactose-type C-type lectin (MGL) on immune
cells leads to immunosuppressive effects, facilitating immune
evasion and cancer metastasis (28-30)
(Fig. 3B). Therefore, high MUC-1
levels were markedly associated with decreased patient OS and were
correlated with tumor extension and pleural invasion (19,20).
It has been suggested that MUC-1 acts as a signaling molecule
involved in the regulation of apoptosis through its interaction
with the BAX protein (31)
(Fig. 3G). The C-terminal of MUC-1
interacts with EGFR and other receptor tyrosine kinases (RTKs),
leading to downstream signaling activation that promotes EMT,
cancer stem cell formation and inflammatory memory. These
mechanisms contributed to resistance to osimertinib, although there
are additional pathways that explain this drug resistance. For
example, the WNT/β-catenin, NF-κB and JAK1/STAT3 pathways, which
induce EMT, stemness, and inflammatory signaling and engage RTK-RAS
effectors such as PI3K and GRB2/SOS to enhance proliferative and
survival signaling. These molecules also recruit chromatin
remodeling complexes polycomb repressive complex 1 and 2 (PRC1/2)
and SWItch/sucrose non-fermentable (SWI/SNF) that cooperate with
JUN/AP-1 to promote pluripotency factors, lineage plasticity and
drug resistance (32) (Fig. 3C).
Exosomal MUC-1 was preferentially found in NSCLC
cells, suggesting a role in shaping the TME and evading immunity
(22). Its level was nearly nine
times higher than the total cellular membrane-associated MUC-1. The
elevated plasma exosomal MUC-1 levels distinguished NSCLC patients
from healthy individuals more accurately than total plasma MUC-1,
highlighting its promising noninvasive biomarker (22). Cell-surface and exosomal MUC-1 both
contributed to tumor progression, therapeutic resistance and immune
modulation (18).
Subtype-specific differences were observed in NSCLC.
Subgroup meta-analyses according to tumor subtype were planned.
However, the limited number of eligible studies precluded a
meaningful quantitative synthesis. Therefore, these differences
were described narratively. Mito et al (13) reported that high TROP-2 expression
was markedly correlated with poor clinical outcomes in ADC
patients, but not in SCC patients (13). The researchers suggested that SCC is
more resistant to the immune system due to its mutations, which may
explain the different outcomes. Similarly, Jiang et al
(18) found that high expression of
MUC-1-C was predominantly observed in women, non-smokers, ADC (but
not SCC) and patients with advanced-stage ADC (27). The mechanism for this finding may
involve MUC-1-C activating oncogenic pathways such as
PI3K/AKT/mTOR, NF-κB, and Wnt/β-catenin, which enhance
proliferation, metastasis, and immune evasion and are more active
in ADC than in SCC (8,30).
Notably, the expression of MUC-1 stimulates the
expression of TROP-2 through an interaction between galectin-3, an
endogenous ligand, and MUC-1(27).
This binding attracts Sp1 and promotes binding between Sp1 and the
TROP-2 promoter, resulting in an increased TROP-2 expression
(10) (Fig. 3F). Therefore, there is a high
potential that cancer cells that have a high MUC-1 may also have
high TROP-2. The preliminary data in our cohort containing 109
NSCLC cases depicted 80% of total cases had high expression of both
antigens. Mechanistically, cancer cells with high levels of both
TROP-2 and MUC-1 have more aggressive tumorigenic properties to
invade and metastasize (8,9). Hence, the co-regulation of TROP-2 and
MUC-1 through galentin-3 may provide a biological rationale for why
both markers, when evaluated together in an exploratory pooled
analysis, were associated with poor survival outcomes in NSCLC
patients.
The overall meta-analysis suggested a statistically
significant association between biomarker overexpression and poorer
survival outcomes. Leave-one-out sensitivity analysis demonstrated
that exclusion of any single study did not materially alter the
pooled effect estimates and the overall associations remained
statistically significant, supporting the reliability of the
findings. However, the limited number of included studies due to
the PICO inclusion criteria combined with the existing survival
statistics, particularly for TROP-2 (n=2) and MUC-1 (n=3), warrants
careful interpretation of the results. Although statistical
heterogeneity was low in the individual biomarker analyses (I²=20%
for TROP-2 and I²=0% for MUC-1), the small number of studies may
limit the interpretability of the I² statistic and may not fully
capture potential between-study variability. Therefore, an
additional sensitivity analysis using a random-effects model, which
accounts for both within-study and between-study variability, was
performed. The results were consistent with those obtained using
the fixed-effect model, with no changes in the direction or
statistical significance of the associations (Table V). For the exploratory pooled
analysis of TROP-2 and MUC-1, moderate heterogeneity was observed
(I²=40%), which may reflect biological and methodological
differences between studies evaluating the two biomarkers. Notably,
because no included study simultaneously assessed TROP-2 and MUC-1
within the same patient cohort, this analysis should not be
interpreted as evidence of a dual-biomarker effect or
co-expression.
Clinically, both TROP-2 and MUC-1 have emerged as
actionable targets. TROP-2 has been applied as a targeted therapy
in the form of antibody drug conjugates, such as datopotamab
deruxtecan, a TROP-2-directed monoclonal antibody covalently linked
to a topoisomerase I inhibitor (Fig.
3). In phase 3 of the clinical trial, this antibody drug
conjugate was found to markedly improve PFS compared with docetaxel
(33). Moreover, sacituzumab
govitecan, another TROP-2 antibody drug conjugate that selectively
delivers SN-38 (an active metabolite of irinotecan), also showed
numerically improved OS with favorable tolerability (34). Other therapeutic strategies include
TGF-β inhibitors (such as vactosertib) and Akt inhibitors (such as
MK-2206 and perifosine), which target downstream TROP-2 pathways.
TGF-β production, which inhibits Smad/p63 signaling, has been
targeted using TGF-β signaling inhibitors such as antisense
oligonucleotides and small-molecule inhibitors such as vactosertib
(25) (Fig. 3). The IGF2/IGF1R/Akt axis has been
targeted using Akt inhibitors, including the selective Akt
inhibitor (MK-2206) and the Akt translocation inhibitor
(perifosine) (35).
For MUC-1, therapeutic approaches include Chimeric
antigen receptor T-cells (CAR T-cells). A study by Wei et al
(36) developed prostate stem cell
antigen-redirected CAR T-cells and MUC-1-redirected CAR T-cells and
found antitumor activity; a synergistic effect was observed when
used as combined therapy. Moreover, the aforementioned mechanism
pathways of MUC-1 have also been applied as targeted therapies.
NF-κB-induced PD-L1 activation, which leads to T-cell exhaustion,
has been targeted using PD-L1 inhibitors such as atezolizumab and
durvalumab (37,38), and PD-1 inhibitors such as
pembrolizumab and nivolumab (39,40)
(Fig. 3). Since MUC-1 interacts
with the BAX protein involved in apoptosis regulation, BAX
upregulation has been used for treatment, for example, navitoclax
(Bcl-2/Bcl-xL inhibitor) (41), and
vorinostat (pan-histone deacetylase inhibitor) (42). MUC-1 interacts with EGFR and other
RTKs, which have been widely used as targets of therapy,
particularly EGFR inhibitors such as EGFR-tyrosine kinase
inhibitors (EGFR-TKIs), such as gefitinib and osimertinib (43). One component of MUC-1 is Galectin-3,
which can activate pathways of other RTKs and induce TROP-2
synthesis. Galectin-3 has been targeted using galectin-3
inhibitors, which can block tumor growth and modulate T-cell
function. Furthermore, synergistic antitumor activity has been
observed when galectin-3 inhibitors are combined with PD-L1
blockade (44) (Fig. 3).
The present systematic review and meta-analysis
offered insights into the prognostic role of TROP-2 and MUC-1 in
NSCLC. However, several limitations should be considered. The
limited number of studies (n=12) were included, and the potential
specific search term use may have resulted in the omission of
relevant studies, leading to publication bias. Therefore, the
findings should be interpreted cautiously. In addition, although
several studies (21,22) were rated as fair quality according
to the NOS, they still met the predefined inclusion criteria and
reported relevant outcome data. Their findings were consistent with
those of lower risk of bias studies, and their inclusion did not
meaningfully affect the pooled estimates.
Several important limitations must be considered
when interpreting the results of the present study. First, no
included study simultaneously evaluated the expression of TROP-2
and MUC-1 within the same patient cohort. Therefore, the present
pooled analysis should not be interpreted as evidence of a true
dual-biomarker effect and further prospective studies are needed to
evaluate both biomarkers in the same population to clarify their
potential combined prognostic value. Furthermore, there is
considerable clinical and methodological heterogeneity among the
included studies. The studies differed substantially in specimen
types (including tumor tissue, blood/plasma, exosomes and RNA-based
datasets), detection methods and cut-off definitions, all of which
may affect the comparability of reported hazard ratios. Clinical
characteristics, such as NSCLC histological subtype, disease stage
and treatment backgrounds, also varied widely. Consequently, while
the present pooled analysis provided an overall estimate of
prognostic significance, these findings do not originate from a
homogeneous clinical setting and must be generalized and
interpreted with caution.
Future studies should place greater emphasis on the
evaluation of longitudinal and dynamic assessment of biomarkers.
Adequately designed prospective studies are needed that incorporate
serial measurements, paired pre- and post-treatment tissue samples
and standardized detection techniques to improve the
characterization of treatment-related changes in TROP-2 and MUC-1
expression over time. Additionally, integrating dynamic biomarker
data into prognostic models can enhance risk stratification and
treatment selection. Importantly, studies that evaluate both
biomarkers simultaneously within the same patient cohorts are
necessary to validate their combined prognostic and predictive
value and to enhance the clinical and translational applicability
of these markers in NSCLC.
In conclusion, the present systematic review and
meta-analysis suggested that elevated expression of either TROP-2
or MUC-1 in NSCLC is associated with poorer survival and more
aggressive clinicopathological features. Furthermore, an
exploratory pooled analysis of both biomarker groups indicates a
potential association between biomarker expression and worse
survival outcomes, highlighting the need for further investigation
of their prognostic value as a dual biomarker strategy. Future
studies that simultaneously assess TROP-2 and MUC-1 expression
within the same patient cohorts are warranted to validate whether
their co-expression provides additional prognostic information
beyond individual biomarker assessment. While the potential for a
dual assessment of TROP-2 and MUC-1 to enhance risk stratification
requires further validation through prospective studies, existing
mechanistic evidence supports a potential role for their
coordinated involvement in tumor progression, immune escape and
resistance to therapy. Together, these preliminary findings provide
a clinical suggestion for further investigating TROP-2 and MUC-1 as
potential therapeutic targets. Continued exploration of directed
strategies, including antibody-drug conjugates, CAR T-cell
approaches, and pathway-focused inhibitors, is warranted to
determine if they can ultimately improve the precision of treatment
for patients with NSCLC.
Acknowledgements
The authors gratefully acknowledge Dr James Mark
Simmerman, Mahidol University, Bangkok, Thailand, for editing the
manuscript.
Funding
Funding: The present study was supported by the NSRF via the
Program Management Unit for Human Resources and Institutional
Development, Research and Innovation (grant no. B38G670007).
Availability of data and materials
Not applicable.
Authors' contributions
PN, JL, NS and KS performed the data curation
(including literature search, study selection, data extraction and
quality assessment), conducted the formal analysis and wrote the
original draft of the manuscript. RW, PT, RK and CT contributed to
the writing, reviewing and editing of the manuscript. RW and RK
performed the validation of the present study. CT was responsible
for conceptualization, the formal analysis and the final revision
of the manuscript. Data authentication is not applicable. All
authors read and approved the final manuscript.
Ethics approval and consent to
participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing
interests.
Use of artificial intelligence tools
During the preparation of this work, artificial
intelligence tools were used to improve the readability and
language of the manuscript or to generate images, and subsequently,
the authors revised and edited the content produced by the
artificial intelligence tools as necessary, taking full
responsibility for the ultimate content of the present
manuscript.
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