Reannotation and Analysis of Clinical and Chemotherapy Outcomes in the Ovarian Data Set From The Cancer Genome Atlas

Abstract

Purpose The ovarian cancer data set from The Cancer Genome Atlas integrates genomic and proteomic data with clinical annotations based on chart abstractions. We aimed to develop an algorithm to create a matching, more accessible clinical data set cataloging time to treatment failure (TTF) of sequential lines of treatment in patients with serous ovarian cancers. Materials and Methods The master data set of 587 patients with serous ovarian cancer was condensed into a more homogeneous and clinically relevant population comprised of high-risk patients with both grade 3 cancers and stage III or IV disease, resulting in a subgroup of 450 patients. We quantified the TTF of different lines of therapy as well as different therapeutic combinations by extrapolating from the time of starting one therapy to the time of starting a subsequent therapy. Results The overall survival (OS) of patients was highly related to platinum sensitivity status, with median OS times of 56.6, 27.0, and 11.6 months in patients who had platinum-sensitive, -resistant, or -refractory disease, respectively. In high-risk patients, the median TTFs were 14.8, 10.2, 5.7, and 4.1 months with the first, second, third, and fourth lines of chemotherapy, respectively. Patients with stable disease after first-line therapy had similar OS outcomes as patients with partial remissions (34.4 v 33.7 months, respectively). Conclusion This new data set enhances the clinical annotation by providing exploitable chemotherapy benefit data that can now be paired with genomic and proteomic data within The Cancer Genome Atlas data. The major determinant of OS in this study was platinum sensitivity status. TTF decreased with each successive line of therapy. However, patients who achieved only stable disease with first-line therapy had OS similar to those with partial remission.

Distinct fibroblast functional states drive clinical outcomes in ovarian cancer and are regulated by TCF21

“…The same is true regardless of whether the 75% (top) or 50% cutoff (bottom) is applied. (F) A subset of TCGA patients could be classified into groups based on their response to chemotherapy, as described in Villalobos et al (2018) . Comparison of these classifications with the FAP-high ( n = 61) and FAP-low ( n = 18) patients revealed that complete responses were more frequent in FAP-low patients (*, P = 0.023, Fisher’s exact test).…”

“…4 E ). To specifically investigate the relationship between FAP-high and FAP-low CAFs and chemotherapy response, we used a study that annotated TCGA patients into the following categories based on their response to treatment: complete response, partial response, stable disease, progressive disease, or refractory ( Villalobos et al, 2018 ). A comparison of FAP-high and FAP-low patients showed that a significantly higher proportion of FAP-low patients demonstrated a complete response to chemotherapy ( Fig.…”

Aberrant transcript usage induces homologous recombination deficiency and predicts therapeutic responses

“…By using the reannotation of clinical outcomes of TCGA cases (n = 103) 57 , we evaluated the performance of our tHRD model in predicting platinum sensitivity (Supplementary Table 3). In comparison to gHRD, the tHRD prediction exhibited an improvement in terms of the precision and recall metrics as well as the accuracy and F1 score (Fig.…”

Insights into Impact of DNA Copy Number Alteration and Methylation on the Proteogenomic Landscape of Human Ovarian Cancer via a Multi-omics Integrative Analysis

“…Despite the tremendous efforts on reproducible delineation of molecular HGSOC subsets through large-scale next-generation sequencing profilings (28, 54 -56), understanding of the mechanisms of oncogenic alterations of HGSOC is still limited and there is still a lack of therapeutically actionable genomic alterations in tumors (53,57). Novel strategies are needed to gain insights that could lead to new treatment targets.…”