{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T19:40:32Z","timestamp":1786390832296,"version":"build-2736575974"},"reference-count":34,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:00:00Z","timestamp":1781222400000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Reports"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Systemic cervical cancer management continues to be challenging. Numerous chemotherapies have been approved, but predicting response is difficult due to the lack of biomarkers. Here, we analyze the genetic and protein profiles of 20 cervical cancer cell lines (CCCLs) and explore their correlation with drug response patterns to commonly used drugs, aiming to identify novel biomarkers of treatment response or resistance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Material and Methods<\/jats:title>\n                    <jats:p>Twenty cell lines (CLs) were characterized for HPV type, for genetic alterations, and protein expression profiles. Pharmacoprofiling in 10 selected CLs was carried out against 34 drugs used in the clinic, assessing drug concentrations needed to reach half maximal inhibitory concentration (IC50) in nanomolar and micromolar ranges. Subtractive bioinformatics analyses aimed to identify genetic alterations (609 genes of clinical interest), associated with CL drug resistance or on the contrary with synthetic lethality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Despite a small sample size, genetic alteration frequencies and types of CCCLs were in line with those in clinical samples, except for the detection of a higher frequencyin specific genetic alterations such as\n                      <jats:italic>NBPF1<\/jats:italic>\n                      and\n                      <jats:italic>STK11<\/jats:italic>\n                      in CLs. Pharmacological screening identified drugs exhibiting therapeutic activity in most CLs while others were highly selective. Bioinformatics analyses suggested, loss\u2010of\u2010function (LoF) alterations in\n                      <jats:italic>PAPBC3<\/jats:italic>\n                      in CLs sensitive to microtubule interfering agentsin addition to 50 variably present alterations in the microtubule pathway. LoF alterations in\n                      <jats:italic>CSMD3, OBSCN, ZNF 717, ALPK2, CLDND1, GTF3A, NLRP1, SI,<\/jats:italic>\n                      and\n                      <jats:italic>TRIM66<\/jats:italic>\n                      were associated with Epigenetic acting drug activity and LoF of\n                      <jats:italic>OSBPL1A<\/jats:italic>\n                      with Eprenetapopt (APR\u2010246) activity. Drug synergistic effects were observed with certain drug combinations.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This paper reports genetic variants in 20 CLs as well as the results of the assessment on whether those variants may help predict response or resistance to certain drug families. With a few exceptions, genetic alteration frequency in CCCLs, conducted in the same analytical batches, compares favorably with published patient data. Results need confirmation in independent larger studies both in CLs and in clinical settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cnr2.70599","type":"journal-article","created":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T04:50:47Z","timestamp":1781326247000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unveiling Candidate Markers for Drug Resistance or Synthetic Lethality in Cervical Cancer: Integrative Analysis of Genetic and Pharmacoprofiling"],"prefix":"10.1002","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0277-6219","authenticated-orcid":false,"given":"Suzy","family":"Scholl","sequence":"first","affiliation":[{"name":"Department of Drug Development and Innovation (D3i) Institut Curie, Paris\u2010Saclay University  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elaine Del","family":"Nery","sequence":"additional","affiliation":[{"name":"Biophenics High\u2010Content Screening Laboratory, PICT\u2010IBiSA, Paris Biofoundry\/UMR168 Department of Translational Research, Institut Curie, PSL Research University  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre","family":"Gestraud","sequence":"additional","affiliation":[{"name":"Computational Oncology, PSL Research University, Mines Paris Tech, INSERM U1331  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maral","family":"Halladjian","sequence":"additional","affiliation":[{"name":"Department of Drug Development and Innovation (D3i) Institut Curie, Paris\u2010Saclay University  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8737-5371","authenticated-orcid":false,"given":"Elodie","family":"Girard","sequence":"additional","affiliation":[{"name":"Computational Oncology, PSL Research 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