|
1
|
Akram M, Iqbal M, Daniyal M and Khan AU:
Awareness and current knowledge of breast cancer. Biol Res.
50:332017. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Kolak A, Kamińska M, Sygit K, Budny A,
Surdyka D, Kukiełka-Budny B and Burdan F: Primary and secondary
prevention of breast cancer. Ann Agric Environ Med. 24:549–553.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Barzaman K, Karami J, Zarei Z,
Hosseinzadeh A, Kazemi MH, Moradi-Kalbolandi S, Safari E and
Farahmand L: Breast cancer: Biology, biomarkers, and treatments.
Int Immunopharmacol. 84:1065352020. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Derakhshan F and Reis-Filho JS:
Pathogenesis of triple-negative breast cancer. Annu Rev Pathol.
17:181–204. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Yin L, Duan JJ, Bian XW and Yu SC:
Triple-negative breast cancer molecular subtyping and treatment
progress. Breast Cancer Res. 22:612020. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Howard FM and Olopade OI: Epidemiology of
triple-negative breast cancer: A review. Cancer J. 27:8–16. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Russo A, Incorvaia L, Capoluongo E,
Tagliaferri P, Gori S, Cortesi L, Genuardi M, Turchetti D, De
Giorgi U, Di Maio M, et al: Implementation of preventive and
predictive BRCA testing in patients with breast, ovarian,
pancreatic, and prostate cancer: A position paper of Italian
scientific societies. ESMO Open. 7:1004592022. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Copson ER, Maishman TC, Tapper WJ, Cutress
RI, Greville-Heygate S, Altman DG, Eccles B, Gerty S, Durcan LT,
Jones L, et al: Germline BRCA mutation and outcome in young-onset
breast cancer (POSH): A prospective cohort study. Lancet Oncol.
19:169–180. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Gagliardi F, Narayanan A and Mortini P:
SPARCL1 a novel player in cancer biology. Crit Rev Oncol Hematol.
109:63–68. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
He K, Li C, Yuan H, Jiang K and Deng G:
Immunological role and prognostic value of SPARCL1 in pan-cancer
analysis. Pathol Oncol Res. 28:16106872022. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Zhou Y and Zhang Q: Association of tumor
suppressor sparcl1 with clinical staging and prognosis of NSCLC.
Ann Clin Lab Sci. 51:756–765. 2021.PubMed/NCBI
|
|
12
|
Hu H, Cai W, Zheng S and Ge W: SPARCL1, a
novel prognostic predictive factor for GI malignancies: a
meta-analysis. Cell Physiol Biochem. 44:1485–1496. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Cao F, Wang K, Zhu R, Hu YW, Fang WZ and
Ding HZ: Clinicopathological significance of reduced SPARCL1
expression in human breast cancer. Asian Pac J Cancer Prev.
14:195–200. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Chen M, Zheng W and Fang L: Identifying
liver metastasis-related hub genes in breast cancer and
characterizing SPARCL1 as a potential prognostic biomarker. PeerJ.
11:e153112023. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Su Z, Wang G and Li L: CHRDL1, NEFH, TAGLN
and SYNM as novel diagnostic biomarkers of benign prostatic
hyperplasia and prostate cancer. Cancer Biomark. 38:143–159. 2023.
View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Oliveras-Ferraros C, Vazquez-Martin A,
Cuyàs E, Corominas-Faja B, Rodríguez-Gallego E, Fernández-Arroyo S,
Martin-Castillo B, Joven J and Menendez JA: Acquired resistance to
metformin in breast cancer cells triggers transcriptome
reprogramming toward a degradome-related metastatic stem-like
profile. Cell Cycle. 13:1132–1144. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Chandrashekar DS, Karthikeyan SK, Korla
PK, Patel H, Shovon AR, Athar M, Netto GJ, Qin ZS, Kumar S, Manne
U, et al: UALCAN: An update to the integrated cancer data analysis
platform. Neoplasia. 25:18–27. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Chandrashekar DS, Bashel B, Balasubramanya
SAH, Creighton CJ, Ponce-Rodriguez I, Chakravarthi BVSK and
Varambally S: UALCAN: A portal for facilitating tumor subgroup gene
expression and survival analyses. Neoplasia. 19:649–658. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Chen F, Zhang Y, Chandrashekar DS,
Varambally S and Creighton CJ: Global impact of somatic structural
variation on the cancer proteome. Nat Commun. 14:56372023.
View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Tang Z, Kang B, Li C, Chen T and Zhang Z:
GEPIA2: An enhanced web server for large-scale expression profiling
and interactive analysis. Nucleic Acids Res 47 (W1). W556–W560.
2019. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Jézéquel P, Campone M, Gouraud W,
Guérin-Charbonnel C, Leux C, Ricolleau G and Campion L:
bc-GenExMiner: An easy-to-use online platform for gene prognostic
analyses in breast cancer. Breast Cancer Res Treat. 131:765–775.
2012. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Jézéquel P, Gouraud W, Ben Azzouz F,
Guérin-Charbonnel C, Juin PP, Lasla H and Campone M: bc-GenExMiner
4.5: New mining module computes breast cancer differential gene
expression analyses. Database (Oxford). 2021:baab0072021.
View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Prat A, Pineda E, Adamo B, Galván P,
Fernández A, Gaba L, Díez M, Viladot M, Arance A and Muñoz M:
Clinical implications of the intrinsic molecular subtypes of breast
cancer. Breast. 24 (Suppl 2):S26–S35. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Győrffy B: Survival analysis across the
entire transcriptome identifies biomarkers with the highest
prognostic power in breast cancer. Comput Struct Biotechnol J.
19:4101–4109. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Li T, Fu J, Zeng Z, Cohen D, Li J, Chen Q,
Li B and Liu XS: TIMER2.0 for analysis of tumor-infiltrating immune
cells. Nucleic Acids Res 48 (W1). W509–W514. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Livak KJ and Schmittgen TD: Analysis of
relative gene expression data using real-time quantitative PCR and
the 2(−Delta Delta C(T)) method. Methods. 25:402–408. 2001.
View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Kim YM, Kang M, Choi JH, Lee BH, Kim GH,
Ohn JH, Kim SY, Park MS and Yoo HW: A review of the literature on
common CYP17A1 mutations in adults with 17-hydroxylase/17,20-lyase
deficiency, a case series of such mutations among Koreans and
functional characteristics of a novel mutation. Metabolism.
63:42–49. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Vasaikar SV, Straub P, Wang J and Zhang B:
LinkedOmics: Analyzing multi-omics data within and across 32 cancer
types. Nucleic Acids Res. 46(D1): D956–D963. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Edge SB and Compton CC: The American joint
committee on cancer: The 7th edition of the AJCC cancer staging
manual and the future of TNM. Ann Surg Oncol. 17:1471–1474. 2010.
View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Olawaiye AB, Baker TP, Washington MK and
Mutch DG: The new (version 9) American joint committee on cancer
tumor, node, metastasis staging for cervical cancer. CA Cancer J
Clin. 71:287–298. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Stanton SE and Disis ML: Clinical
significance of tumor-infiltrating lymphocytes in breast cancer. J
Immunother Cancer. 4:592016. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Lu H, Lou H, Wengert G, Paudel R, Patel N,
Desai S, Crum B, Linton-Reid K, Chen M, Li D, et al: Tumor and
local lymphoid tissue interaction determines prognosis in
high-grade serous ovarian cancer. Cell Rep Med. 4:1010922023.
View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Thorat MA and Balasubramanian R: Breast
cancer prevention in high-risk women. Best Pract Res Clin Obstet
Gynaecol. 65:18–31. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Winters S, Martin C, Murphy D and Shokar
NK: Breast cancer epidemiology, prevention, and screening. Prog Mol
Biol Transl Sci. 151:1–32. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Maughan KL, Lutterbie MA and Ham PS:
Treatment of breast cancer. Am Fam Physician. 81:1339–1346.
2010.PubMed/NCBI
|
|
36
|
Peart O: Breast intervention and breast
cancer treatment options. Radiol Technol. 86:535M–562M.
2015.PubMed/NCBI
|
|
37
|
Ben-Dror J, Shalamov M and Sonnenblick A:
The history of early breast cancer treatment. Genes (Basel).
13:9602022. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Tesch ME and Partridge AH: Treatment of
breast cancer in young adults. Am Soc Clin Oncol Educ Book.
42:1–12. 2022.PubMed/NCBI
|
|
39
|
Zhang HP, Wu J, Liu ZF, Gao JW and Li SY:
SPARCL1 is a novel prognostic biomarker and correlates with tumor
microenvironment in colorectal cancer. Biomed Res Int.
2022:13982682022. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Yu Y, Chen Y, Ma J, Yu X, Yu G and Li Z:
SPARCL1 is a novel predictor of tumor recurrence and survival in
hilar cholangiocarcinoma. Tumour Biol. 37:4159–4167. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Gao S, Gang J, Yu M, Xin G and Tan H:
Computational analysis for identification of early diagnostic
biomarkers and prognostic biomarkers of liver cancer based on GEO
and TCGA databases and studies on pathways and biological functions
affecting the survival time of liver cancer. BMC Cancer.
21:7912021. View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Li H, Lei Y, Li G and Huang Y:
Identification of tumor-suppressor genes in lung squamous cell
carcinoma through integrated bioinformatics analyses. Oncol Res.
32:187–197. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Yang H, Zou X, Yang S, Zhang A, Li N and
Ma Z: Identification of lactylation related model to predict
prognostic, tumor infiltrating immunocytes and response of
immunotherapy in gastric cancer. Front Immunol. 14:11499892023.
View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Zhao H, Luo K, Liu M, Cai Y, Liu S, Li S,
Zhao Y and Zhang H: Immune regulation and prognostic prediction
model establishment and validation of PSMB6 in lung adenocarcinoma.
Front Genet. 15:14580472024. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Xiao X, Peng J, Chen Y, Lu X, Sun W, Xiao
W, Yuan M and Huang X: Comprehensive analysis of differential gene
expression and correlated immune infiltration in bladder cancer.
Iran J Public Health. 52:1225–1237. 2023.PubMed/NCBI
|
|
46
|
Chen Z, Sun X, Kang Y, Zhang J, Jia F, Liu
X and Zhu H: A novel risk model based on the correlation between
the expression of basement membrane genes and immune infiltration
to predict the invasiveness of pituitary adenomas. Front Endocrinol
(Lausanne). 13:10797772023. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Zhao G, Gentile ME, Xue L, Cosgriff CV,
Weiner AI, Adams-Tzivelekidis S, Wong J, Li X, Kass-Gergi S,
Holcomb NP, et al: Vascular endothelial-derived SPARCL1 exacerbates
viral pneumonia through pro-inflammatory macrophage activation.
bioRxiv [Preprint]. 2023.05.25.541966. 2023.
|
|
48
|
Strunz M, Jarrell JT, Cohen DS, Rosin ER,
Vanderburg CR and Huang X: Modulation of SPARC/hevin proteins in
Alzheimer's disease brain injury. J Alzheimers Dis. 68:695–710.
2019. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Sheybani ND, Witter AR, Garrison WJ,
Miller GW, Price RJ and Bullock TNJ: Profiling of the immune
landscape in murine glioblastoma following blood brain/tumor
barrier disruption with MR image-guided focused ultrasound. J
Neurooncol. 156:109–122. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
50
|
Sadique FL, Subramaiam H, Krishnappa P,
Chellappan DK and Ma JH: Recent advances in breast cancer
metastasis with special emphasis on metastasis to the brain. Pathol
Res Pract. 260:1553782024. View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Ersahin T, Tuncbag N and Cetin-Atalay R:
The PI3K/AKT/mTOR interactive pathway. Mol Biosyst. 11:1946–1954.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
52
|
Xu F, Na L, Li Y and Chen L: Roles of the
PI3K/AKT/mTOR signalling pathways in neurodegenerative diseases and
tumours. Cell Biosci. 10:542020. View Article : Google Scholar : PubMed/NCBI
|
|
53
|
Carnero A, Blanco-Aparicio C, Renner O,
Link W and Leal JF: The PTEN/PI3K/AKT signalling pathway in cancer,
therapeutic implications. Curr Cancer Drug Targets. 8:187–198.
2008. View Article : Google Scholar : PubMed/NCBI
|
|
54
|
Li G, Zhang C, Liang W, Zhang Y, Shen Y
and Tian X: Berberine regulates the Notch1/PTEN/PI3K/AKT/mTOR
pathway and acts synergistically with 17-AAG and SAHA in SW480
colon cancer cells. Pharm Biol. 59:21–30. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
55
|
Zhu L, Yang F, Wang G and Li Q: CXC motif
chemokine receptor type 4 disrupts blood-brain barrier and promotes
brain metastasis through activation of the PI3K/AKT pathway in lung
cancer. World Neurosurg. 166:e369–e381. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
56
|
Tusup M, Kündig TM and Pascolo S:
Epitranscriptomics modifier pentostatin indirectly triggers
Toll-like receptor 3 and can enhance immune infiltration in tumors.
Mol Ther. 30:1163–1170. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
57
|
Pan M, Wei X, Xiang X, Liu Y, Zhou Q and
Yang W: Targeting CXCL9/10/11-CXCR3 axis: An important component of
tumor-promoting and antitumor immunity. Clin Transl Oncol.
25:2306–2320. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
58
|
Wu J, Yang S, Gou F, Zhou Z, Xie P, Xu N
and Dai Z: Intelligent segmentation medical assistance system for
MRI images of osteosarcoma in developing countries. Comput Math
Methods Med. 2022:77035832022.PubMed/NCBI
|
|
59
|
Gygi JP, Kleinstein SH and Guan L:
Predictive overfitting in immunological applications: Pitfalls and
solutions. Hum Vaccin Immunother. 19:22518302023. View Article : Google Scholar : PubMed/NCBI
|
