Evidence blocks for effective presentation of genomic findings at molecular tumor boards: Single institution experience

Genomic profiling, or molecular profiling of the tumor, is becoming a key component of therapeutic decision making in clinical oncology, and is typically carried out via next generation sequencing. However, the interpretation of the results and evaluation of rationale for targeting the uncovered alterations is challenging and requires a deep understanding of cancer biology, genetics, genomics and oncology. Multidisciplinary molecular tumor boards represent a promising strategy in the facilitation of molecularly-informed therapeutic decisions, and usually consist of specialists with various fields of expertise. To effectively communicate the biological and clinical significance of genomic findings, as well as to make molecular tumor board discussions more productive, we developed and implemented evidence blocks into case discussions in our center. We found that this approach facilitated clinicians' understanding of the results of genomic profiling, and resulted in shorter yet more efficient case discussions within the molecular tumor board. Here, we discuss our experience with evidence blocks and how their implementation influenced the molecular tumor board practice.

Utility of public knowledge bases for the interpretation of comprehensive tumor molecular profiling results

With the growing use of comprehensive tumor molecular profiling (CTMP), the therapeutic landscape of cancer is rapidly evolving. NGS produces large amounts of genomic data requiring complex analysis and subsequent interpretation. We sought to determine the utility of publicly available knowledge bases (KB) for the interpretation of the cancer mutational profile in clinical practice. Analysis was performed across patients who previously underwent CTMP. Independent interpretation of the CTMP was performed manually, and then, the recommendations were compared to ones present in KBs (OncoKB, CIViC, CGI, CGA, VICC, MolecularMatch). A total of 222 CTMP reports from 222 patients with 932 genomic alterations (GA) were identified. For 368 targetable GA identified in 171 (77%) of the patients, 1381 therapy recommendations were compiled. Except for CGA, therapy ESCAT LOE I, II, IIIA and IIIB therapy options were equally represented in the majority of KB. Personalized treatment options with ESCAT LOE I-II were provided for 35 patients (16%); MolecularMatch/CIViC allowed to collect ESCAT I-II treatment options for 34 of them (97%), OncoKB/CGI-for 33 of them (94%). Employing VICC and CGA 6 (17%) and 20 (57%) of patients were left without ESCAT I or II treatment options. For 88 patients with ESCAT level III-B therapy recommendations: only 2 (2%), 3 (3%), 4 (5%) and 6 (7%) of patients were left without options with CIViC, MolecularMatch, CGI and OncoKB, and with VICC-12 (14%). Highest overlap ratio was observed for IIIA (0.81) biomarkers, with the comparable results for LOE I-II. Meanwhile, overlap ratio for ESCAT LOE IV was 0.22. Public KBs provide substantial information on ESCAT-I/R1 biomarkers, but the information on ESCAT II-IV and resistance biomarkers is underrepresented. Manual curation should be considered the gold standard for the CTMP interpretation.

Utility of public Knowledge Bases (KB) for comprehensive tumor molecular profiling (CTMP) result interpretation

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Background: With the spread of CTMP in cancer patient management and expansion of molecular-targeted treatment opportunities, resources for quick and efficient molecular profile interpretation are in high demand. Number of public KBs have been introduced. We analysed their utility to compile per patient treatment recommendations. Methods: Analysis was performed across patients, who underwent CTMP. Based on the reported molecular alterations, interpretation and critical evidence evaluation was performed not taking into account the recommendations provided in the original CTMP reports. Therapy recommendations were ranked according to ESCAT. Resistance biomarkers were ranked according to OncoKB V2 level of evidence system. OncoKB, CIViC, CGI, CGA, VICC and MolecularMatch were assessed. KBs were assessed through API or local copy of KB. Results: A total of 222 CTMP reports from 222 patients (35% - NSCLC; 24% - CRC; 8% - pancreas; 7% - breast; 4% - gastric; 22% - other) were analysed. CTMP was performed in Foundation Medicine (82%) or Atlas Oncology Diagnostics (18%). Across 222 patients 932 molecular alterations were identified. A total of 1394 therapy recommendations were compiled associated with 368 molecular alteration across 171 (77%) patients (112 recommendations ESCAT level I; 908 - ESCAT III-IV; 70 - OncoKB R1). Across 181 ESCAT-I/R1 therapy recommendations 172 (95%) were present in at least 1 KB (92% for ESCAT-I recommendations, 100% - R1) with the VICC providing the highest rate of retrieval (80%), followed by OncoKB (78%), MolecularMatch (70%), CIViC - (69%) and CGI (69%). Only 92 (53%) of ESCAT-I/R1 therapy recommendations were present in all KBs. Across 27 patients with ESCAT-I recommendations, at least 1 therapy recommendation was retrieved in any KB for all patients. ESCAT II-IV therapy recommendations were provided for 161 patients and grouped by drug class, resulting in 457 [biomarker]-[drug class] associations. Of them 346 (75%) were present in at least 1 KB with the VICC providing the highest rate of retrieval (69%), followed by CGI (61%), CGA (56%), OncoKB (48%), CIViC (48%) and MolecularMatch (45%). Of 161 patients, for 24 (15%) no recommendations were retrieved in any KB for any biomarker identified. For random 15 (a total of 68 molecular alterations) patients KBs were assessed manually in order to estimate the average time in use. CGI was the most easily accessible (3.2 min per patient in average), following by CGA (5.6 min), OncoKB (7.2 min), CIViC (26.2 min), and VICC (35.9 min). Conclusions: Public KBs provide substantial information on ESCAT-I/R1 biomarkers and decent information on ESCAT II-IV biomarkers, reasoning manual curation. VICC provided the most complete information, though was thorough for manual use. The use of multiple KBs may significantly improve retrieval results, though is time-consuming and results in excess of misleading/outdated recommendations.

Gender distribution of speakers and moderators at the Russian cancer congresses in 2016-2021

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Background: Gender equity in world medicine has recently received widespread attention. There is evidence that men and women may practice medicine differently, and better women representation in the oncology workforce and leadership may improve patient outcomes. Nevertheless, women continue to be under-represented in the big academic events, also in oncology. Methods: A retrospective analysis of the programs of major annual Russian oncological congresses: Russian Oncology Congress and White Nights was carried out. The gender of speakers and moderators was collected from 2016 to 2021. Participation of the same person in several sessions or in different roles in one session was considered as a separate case. Data are presented by descriptive statistics, and differences between groups were assessed using the Сhi-square test. P-values below 0.05 were considered statistically significant. Results: The data of 1350 sessions, 796 moderators and 1756 speakers were available for analysis. For the analyzed period of time (2016-2021), the total percentage of female speakers was 42.2% (n = 3120), the percentage of female moderators was 34.8% (n = 1196). There were more male speakers than female speakers in surgical sessions (87.9% and 12.1% p < 0.001). There were more male moderators than women in surgical sessions (92.4% and 7.6% p < 0.001). There were more male speakers than female speakers in chemotherapy sessions (55.2% and 44.8% p < 0.001). There were more male moderators than women in chemotherapy sessions (58.9% and 41.1% p < 0.001). Conclusions: The gender inequality in oncology is more pronounced in the leadership positions in male-dominated specialties such as surgical oncology. Better women representation in the oncology leadership may be an effective strategy to improve oncology care in Russia

Clinical application of next-generation sequencing in cancer patients

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Background: Next-generation sequencing (NGS) has been moving rapidly from pure cancer genomics research towards clinical oncology to provide a rigorous personalized approach to treating cancer. Still there is a number of limitations to overcome before we are ready to fully introduce NGS into everyday clinical decision-making. Here we are sharing our experience with using targeted NGS platforms in clinical practice. Methods: We retrospectively evaluated the NGS results and the treatments, provided to the patients after NGS testing between Marсh 2019 and January 2021. The patients’ clinical characteristics, response to treatment and genomic mutation profiles were reviewed. Coprimary endpoints were the percentage of patients with NGS revealed targeted therapy options and the percentage of patients who received mutation-driven therapy. Results: Samples from 95 patients were tested, most frequently GI tumors (n=25, 26%), hepatobiliary tumors (n=11, 12%), breast cancer (n=10, 11%) gynecological tumors (n=10, 11%), central nervous system tumors (n=7, 7%) and others (n=32, 33%). An average of two gene alterations were identified per patient (range 0-15). The 95% (n=90) of samples had at least one detected mutation, and in 42% (n=40) of cases gene mutations happened to be targetable with existing drugs, including off-label prescriptions. Mutation-driven therapy was performed in 9,5% cases (n=10) with clinically meaningful response in 5 patients (2 patients with ovarian cancer, 2 patients with colon cancer and 1 melanoma). Conclusion: Mutational profiling using a targeted NGS panel has identified potentially targetable alterations in a vast majority of advanced cancer patients. The assay has revealed additional therapeutic options in 42% of patients. However, due to the short-term follow-up, just a small number of patients have received mutation-driven therapy. Further study will be required to determine if the mutation-driven therapy will prove to be clinically meaningful in these patients.

Effectiveness and tolerability of FOLFOXIRI regimen in the third- and subsequent lines of therapy in patients with metastatic colorectal cancer

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Background: Options of therapy are limited for patients with colorectal cancer who developed disease progression during standard 5-FU-, oxaliplatin-, and irinotecan-contained regimens. There is straight information about synergy of irinotecan (SN-38) and oxaliplatin gained from fundamental and early clinical trials. We aimed to analyze effectiveness and safety of triple drug-combination of 5-FU, oxaliplatin and irinotecan (FOLFOXIRI) in heavily pretreated patients with metastatic colorectal cancer. Methods: Patients with a metastatic colorectal cancer who received more than 2 lines of standard 5-FU-, oxaliplatin- and irinotecan-based doublet regimens with or without targeted therapy were included. Reinduction of chemotherapy in previous lines was allowed. The retrospective analysis of medical histories was done. Eligible patients had to receive number of cycles that were sufficient for response rate estimation. Disease response was evaluated according to RECIST 1.1 criteria. Survival analysis was performed using the Kaplan-Meier method. Tolerability was estimated by CTCAE v. 5.0. Results: Forty-six patients were included in retrospective per protocol analysis. The median follow-up was 19 months. The median number of previous lines of chemotherapy was 2 (2-6). Primary resistance to oxaliplatin- and irinotecan-based chemo during previous lines was noted in 20 patients (43%) and 16 patients (35%), respectively, while seven patients (15%) developed the primary resistance to both agents given in a sequential order. All patients were treated with targeted therapy during previous treatment lines. The median of FOLFOXIRI cycles was 8 (range, 2-19). Two patients (4%) were treated with FOLFOXIRI without any targeted agents. The objective response rate was 33% (n = 15). The disease stabilization was reached in 43% (n = 20). The disease control rate was 76% (n = 35). Eleven patients (24%) had the progression of disease at the first follow-up. The median progression free survival and median overall survival were 6 months and 11 months, respectively. Toxicity was evaluated in 35 patients. The most common severe adverse events (grade 3 and 4) were neutropenia (46%) and fatigue (26%). Treatment was delayed in 20 patients (57%), and 13 patients (37%) required dose reduction. One patient had to discontinue treatment due to unacceptable toxicity. Conclusions: According to our study FOLFOXIRI provides the objective response and increased life expectancy in heavily pretreated patients. The further assessment of FOLFOXIRI regimen for refractory colorectal cancer in the prospective trials is needed.

Development of expert system that improve the decision-making process with an emphasis on health-related quality of life in elderly patients with a colon cancer

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Background: Health-Related Quality of Life (HRQoL) is an important issue for elderly patients with colon cancer. We created the expert system which allows to predict low level of HRQoL and accessed it’s quality by using several simulation studies. Methods: We performed a systematic review to figure out the known factors associated with low level of HRQoL in elderly colon cancer patients. The searches were performed in PubMed. We accessed the possible impact of several factors affecting HRQoL, including symptoms, comorbidities and treatment toxicity. All relevant factors were included in prediction model. We assigned the different weights to different factors based on evaluation of clinical studies to develop the logistic regression and Markov stochastic model later. As we needed a binary dependent variable we performed the ROC analysis to figure out an optimal cutoff of HRQoL. Then we simulated a partly virtual dataset based on elderly colon cancer patients diagnosed in Davidovskiy Hospital to evaluate the prediction model quality. All statistical calculations were performed in RStudio. The simulation part was performed using simFrame R package. Results: Twenty two studies with a total number of 2516 patients were included in our systematic review. The 39 factors with different weights were included prediction model with different weights assigned. The weights range varied from 1 to 18.6. The adjusted proportion of summary score's variance (R2 ) varied from 0.09 to 0.47 in univariate analysis. The final logistic regression model quality was moderate: the Nagelkerke R-square coefficient was 57.9. However, the developed model showed a 76% sensitivity and 61% specificity in predicting of lower HRQoL level. Conclusions: Our prediction model allows to prospectively manage of elderly colon cancer patients, making the emphasis on HRQoL. However, the present study has some restrictions: simulation nature of internal validation, possible underestimating of the rare events impact. The long-term comprehensive approach with external validation using large real data analysis is needed to evaluate our prediction model.