Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer

Chowdhury, Shrabanti; Kennedy, Jacob J.; Ivey, Richard G.; Murillo, Óscar; Hosseini, Noshad; Song, Xiaoyu; Petralia, Francesca; Calinawan, Anna; Savage, Sara R.; Berry, Anna B.; Reva, Boris; Özbek, Umut; Krek, Azra; Ma, Wanli; Leprevost, Felipe da Veiga; Ji, Jiayi; Yoo, Seungyeul; Lin, Chenwei; Voytovich, Uliana J.; Huang, Yajue; Lee, Sunhee; Bergan, Lindsay; Lorentzen, Travis D.; Mesri, Mehdi; Rodriguez, Henry; Hoofnagle, Andrew N.; Herbert, Zachary T.; Nesvizhskii, Alexey I.; Zhang, Bing; Whiteaker, Jeffrey R.; Fenyö, David; McKerrow, Wilson; Wang, Joshua; Schürer, Stephan C.; Stathias, Vasileios; Chen, X. Steven; Barcellos-Hoff, Mary Helen; Starr, Timothy K.; Winterhoff, Boris; Nelson, Andrew C.; Mok, Samuel C.; Kaufmann, Scott H.; Cieślik, Marcin; Wang, Pei; Birrer, Michael J.; Paulovich, Amanda G.

doi:10.1016/j.cell.2023.07.004

Cited by 17 publications

(29 citation statements)

References 150 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite thorough genetic analysis of our unique dataset, we did not find genetic drivers behind chemo-refractory phenotype or lack of IFN-I activity, hinting at non-genomic mechanisms behind chemotherapy resistance. Unlike Chowdhury and colleagues 30 , we did not find the LOH of chromosome 17 to be enriched in patients with chemo-refractory HGSC. However, we replicated their finding that BRAF-mutated tumors were exclusively found in the refractory group.…”

Section: Discussioncontrasting

confidence: 99%

Multi-Omics Analysis Reveals the Attenuation of the Interferon Pathway as a Driver of Chemo-Refractory Ovarian Cancer

Afenteva,

Yu,

Rajavuori

et al. 2024

Preprint

View full text Add to dashboard Cite

Ovarian high-grade serous carcinoma (HGSC) represents the deadliest gynecological malignancy, with 10-15% of patients exhibiting primary resistance to first-line chemotherapy. These primarily chemo-refractory patients have particularly poor survival outcomes, emphasizing the urgent need for developing predictive biomarkers and novel therapeutic approaches. Here, we show that interferon type I (IFN-I) pathway activity in cancer cells is a crucial determinant of chemotherapy response in HGSC. Through a comprehensive multi-omics analysis within the DECIDER observational trial (ClinicalTrials.gov identifierNCT04846933) cohort, we identified that chemo-refractory HGSC is characterized by diminished IFN-I and enhanced hypoxia pathway activities. Importantly, IFN-I pathway activity was independently prognostic for patient survival, highlighting its potential as a biomarker. Our results elucidate the heterogeneity of treatment response at the molecular level and suggest that augmentation of IFN-I response could enhance chemosensitivity in refractory cases. This study underscores the potential of the IFN-I pathway as a therapeutic target and advocates for the initiation of clinical trials testing external modulators of the IFN-I response, promising a significant stride forward in the treatment of refractory HGSC.

show abstract

Section: Discussioncontrasting

confidence: 99%

Multi-Omics Analysis Reveals the Attenuation of the Interferon Pathway as a Driver of Chemo-Refractory Ovarian Cancer

Afenteva,

Yu,

Rajavuori

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The resulting coverage profiles were masked for outliers and segmented using CBS as implemented in DNACopy 82 . The resulting segmentation profiles were pruned using CNVEX as described previously 83 . The presence of focal gains was determined by identifying segments >50kb in size with a normalized log-coverage of > 0.5.…”

Section: Methodsmentioning

confidence: 99%

CDK12Loss Promotes Prostate Cancer Development While Exposing Vulnerabilities to Paralog-Based Synthetic Lethality

Tien,

Chang,

Zhang

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

Biallelic loss of cyclin-dependent kinase 12 (CDK12) defines a unique molecular subtype of metastatic castration-resistant prostate cancer (mCRPC). It remains unclear, however, whether CDK12 loss per se is sufficient to drive prostate cancer development, either alone or in the context of other genetic alterations, and whether CDK12-mutant tumors exhibit sensitivity to specific pharmacotherapies. Here, we demonstrate that tissue-specific Cdk12 ablation is sufficient to induce preneoplastic lesions and robust T cell infiltration in the mouse prostate. Allograft-based CRISPR screening demonstrated that Cdk12 loss is positively associated with Trp53 inactivation but negatively associated with Pten inactivation, akin to what is observed in human mCRPC. Consistent with this, ablation of Cdk12 in prostate organoids with concurrent Trp53 loss promotes their proliferation and ability to form tumors in mice, while Cdk12 knockout in the Pten-null prostate cancer mouse model abrogates tumor growth. Bigenic Cdk12 and Trp53 loss allografts represent a new syngeneic model for the study of androgen receptor (AR)-positive, luminal prostate cancer. Notably, Cdk12/Trp53 loss prostate tumors are sensitive to immune checkpoint blockade. Cdk12-null organoids (either with or without Trp53 co-ablation) and patient-derived xenografts from tumors with CDK12 inactivation are highly sensitive to inhibition or degradation of its paralog kinase, CDK13. Together, these data identify CDK12 as a bona fide tumor suppressor gene with impact on tumor progression and lends support to paralog-based synthetic lethality as a promising strategy for treating CDK12-mutant mCRPC.

show abstract

“…Indeed, according to our observation, a lot of glycan misidentifications involved confounding F2 (Fuc [2]) and S (NeuAc), whose masses happen to differ by 1.0204 Da (S mistaken as F2) or −1.0204 Da (F2 substituted by S), as well as the mixup of FS2 (Fuc [1]NeuAc [2]) and G2H2 (HexNAc [2]-Hex [2]) differing by −2.0157 Da. Apparently, the three delta mass clusters could be explained by the glycan misassignment.…”

Section: Need For Xic-based Monoisotope Repickingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Quantitative proteomics concerns discovering significant protein abundance changes at the proteome scale and plays an increasingly important role not only in basic research but also in biomarker discovery for personalized diagnosis and treatment of diseases. 1 In these studies, reproducibility is critical for achieving successful outcomes. Modern high-performance liquid chromatography (LC) and high-resolution tandem mass spectrometry (MS/MS) are relatively mature technologies and a driving force for progress in the field.…”

Section: ■ Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An XIC-Centric Strategy for Improved Identification and Quantification in Proteomic Data Analyses

Wang,

Zhang,

Liu

et al. 2024

J. Proteome Res.

View full text Add to dashboard Cite

Reproducibility is a "proteomic dream" yet to be fully realized. A typical data analysis workflow utilizing extracted ion chromatograms (XICs) often treats the information path from identification to quantification as a one-way street. Here, we propose an XICcentric approach in which the data flow is bidirectional: identifications are used to derive XICs whose information is in turn applied to validate the identifications. In this study, we employed liquid chromatography-mass spectrometry data from glycoprotein and human hair samples to illustrate the XIC-centric concept. At the core of this approach was XIC-based monoisotope repicking. Taking advantage of the intensity information for all detected isotopes across the whole range of an XIC peak significantly improved the accuracy and uncovered misidentifications originating from monoisotope assignment mistakes. It could also rescue non-top-ranked glycopeptide hits. Identification of glycopeptides is particularly susceptible to precursor mass errors for their low abundances, large masses, and glycans differing by 1 or 2 Da easily confused as isotopes. In addition, the XIC-centric strategy significantly reduced the problem of one XIC peak associated with multiple unique identifications, a source of quantitative irreproducibility. Taken together, the proposed approach can lead to improved identification and quantification accuracy and, ultimately, enhanced reproducibility in proteomic data analyses.

show abstract

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer

Cited by 17 publications

References 150 publications

Multi-Omics Analysis Reveals the Attenuation of the Interferon Pathway as a Driver of Chemo-Refractory Ovarian Cancer

Multi-Omics Analysis Reveals the Attenuation of the Interferon Pathway as a Driver of Chemo-Refractory Ovarian Cancer

CDK12Loss Promotes Prostate Cancer Development While Exposing Vulnerabilities to Paralog-Based Synthetic Lethality

An XIC-Centric Strategy for Improved Identification and Quantification in Proteomic Data Analyses

Contact Info

Product

Resources

About