Purpose: To examine whether overall survival (OS) differs for male and female patients with advanced soft-tissue sarcoma (STS).Experimental Design: The study included patients from Kaiser Permanente Northern California and Stanford Cancer Center with grade 2 and 3 locally advanced or metastatic STS whose tumor underwent next-generation sequencing. We used Cox regression modeling to examine association of sex and OS adjusting for other important factors.Results: Among 388 eligible patients, 174 had leiomyosarcoma (LMS), 136 had undifferentiated pleomorphic sarcoma (UPS), and 78 had liposarcoma. OS for male versus female patients appeared to be slightly better among the full cohort [HR = 0.89; 95% confidence interval (CI), 0.66–1.20]; this association appeared to be stronger among the subsets of patients with LMS (HR = 0.76; 95% CI, 0.39–1.49) or liposarcoma (HR = 0.74; 95% CI, 0.32–1.70). Better OS for male versus female patients was also observed among all molecular subgroups except mutRB1 and mutATRX, especially among patients whose tumor retained wtTP53 (HR = 0.73; 95% CI, 0.44–1.18), wtCDKN2A (HR = 0.85; 95% CI, 0.59–1.23), wtRB1 (HR = 0.73; 95% CI, 0.51–1.04), and among patients whose tumor had mutPTEN (HR = 0.37; 95% CI, 0.09–1.62). OS also appeared to be better for males in the MSK-IMPACT and TCGA datasets.Conclusions: A fairly consistent pattern of apparent better OS for males across histologic and molecular subgroups of STS was observed. If confirmed, our results could have implications for clinical practice for prognostic stratification and possibly treatment tailoring as well as for future clinical trials design.

Background: Whether sex and co-mutations impact prognosis of patients with SMARCA4-mutated (mutSMARCA4) malignancies is not clear. Methods: This cohort included patients from Northern California Kaiser Permanente with next-generation sequencing (NGS) performed from August 2020 to October 2022. We used Cox regression modeling to examine the association between sex and overall survival (OS), adjusting for demographics, performance status, Charlson comorbidity index, receipt of treatment, tumor mutation burden (TMB), and TP53, KRAS, CDKN2A, STK11, and Keap1 co-mutations. Results: Out of 9221 cases with NGS performed, 125 cases (1.4%) had a mutSMARCA4. The most common malignancies with a mutSMARCA4 were non-small cell lung cancer (NSCLC, 35.2%), esophageal and stomach adenocarcinoma (12.8%), and cancer of unknown primary (11.2%). The most common co-mutations were p53 (mutp53, 59.2%), KRAS (mutKRAS, 28.8%), CDKN2A (mutCDKN2A, 31.2%), STK11 (mutSTK11, 12.8%), and Keap1 (mutKeap1, 8.8%) mutations. Male patients had substantially worse OS than female patients both among the entire mutSMARCA4 cohort (HR = 1.71, [95% CI 0.92–3.18]) with a median OS of 3.0 versus 43.3 months (p < 0.001), and among the NSCLC subgroup (HR = 14.2, [95% CI 2.76–73.4]) with a median OS of 2.75 months versus un-estimable (p = 0.02). Among all patients with mutSMARCA4, mutp53 versus wtp53 (HR = 2.12, [95% CI 1.04–4.29]) and mutSTK11 versus wtSTK11 (HR = 2.59, [95% CI 0.87–7.73]) were associated with worse OS. Among the NSCLC subgroup, mutp53 versus wtp53 (HR = 0.35, [0.06–1.97]) and mutKRAS versus wtKRAS (HR = 0.04, [0.003-.45]) were associated with better OS, while mutCDKN2A versus wtCDKN2A (HR = 5.04, [1.12–22.32]), mutSTK11 versus wtSTK11 (HR = 13.10, [95% CI 1.16–148.26]), and mutKeap1 versus wtKeap1 (HR = 5.06, [95% CI 0.89–26.61}) were associated with worse OS. Conclusion: In our cohort of patients with mutSMARCA4, males had substantially worse prognosis than females, while mutTP53, mutKRAS, mutCDKN2A, mutSTK11 and mutKeap1were differentially associated with prognosis among all patients and among the NSCLC subgroup. Our results, if confirmed, could suggest potentially unidentified mechanisms that underly this sex and co-mutation-dependent prognostic disparity among patients whose tumor bears a mutSMARCA4.

Immunotherapy response score (IRS) integrates tumor mutation burden (TMB) and quantitative expression biomarkers to predict anti-PD-1/PD-L1 [PD-(L)1] monotherapy benefit. Here, we evaluated IRS in additional cohorts. Patients from an observational trial (NCT03061305) treated with anti-PD-(L)1 monotherapy were included and assigned to IRS-High (-H) versus -Low (-L) groups. Associations with real-world progression-free survival (rwPFS) and overall survival (OS) were determined by Cox proportional hazards (CPH) modeling. Those with available PD-L1 IHC treated with anti-PD-(L)1 with or without chemotherapy were separately assessed. Patients treated with PD-(L)1 and/or chemotherapy (five relevant tumor types) were assigned to three IRS groups [IRS-L divided into IRS-Ultra-Low (-UL) and Intermediate-Low (-IL), and similarly assessed]. In the 352 patient anti-PD-(L)1 monotherapy validation cohort (31 tumor types), IRS-H versus IRS-L patients had significantly longer rwPFS and OS. IRS significantly improved CPH associations with rwPFS and OS beyond microsatellite instability (MSI)/TMB alone. In a 189 patient (10 tumor types) PD-L1 IHC comparison cohort, IRS, but not PD-L1 IHC nor TMB, was significantly associated with anti-PD-L1 rwPFS. In a 1,103-patient cohort (from five relevant tumor types), rwPFS did not significantly differ in IRS-UL patients treated with chemotherapy versus chemotherapy plus anti-PD-(L)1, nor in IRS-H patients treated with anti-PD-(L)1 versus anti-PD-(L)1 + chemotherapy. IRS associations were consistent across subgroups, including both Europeans and non-Europeans. These results confirm the utility of IRS utility for predicting pan-solid tumor PD-(L)1 monotherapy benefit beyond available biomarkers and demonstrate utility for informing on anti-PD-(L)1 and/or chemotherapy treatment. Significance: This study confirms the utility of the integrative IRS biomarker for predicting anti-PD-L1/PD-1 benefit. IRS significantly improved upon currently available biomarkers, including PD-L1 IHC, TMB, and MSI status. Additional utility for informing on chemotherapy, anti-PD-L1/PD-1, and anti-PD-L1/PD-1 plus chemotherapy treatments decisions is shown.

8075 Background: The PI3K/Akt/mTOR axis is deregulated in lymphomas and is an emerging therapeutic target. We previously reported activity of temsirolimus (TEM) in DLBCL and FL (JCO 2010 28(31); however, the response duration was short. Lenalidomide (LEN) is an immunomodulatory agent with multiple anti-tumoral and microenvironmental effects, with activity across lymphoma subtypes. We are thus conducting a phase I/II study of TEM plus escalating doses of LEN. The phase I portion is completed. Methods: Patients (pts) had rel/ref lymphoma after >1 cytotoxic regimen. Other criteria: ANC > 1000/mL, platelets > 75,000/mL, nl renal and hepatic function, no VTE within 3 months, non-pregnant. A standard “3 + 3” design was used with dose levels (DL) listed (Table). TEM was given IV weekly and LEN was dosed orally on D1-D21, q28 days. Dose-limiting toxicity (DLT) was defined as cycle 1 grade 3 or 4 non-hematologic toxicity not responsive to standard supportive care, grade 4 thrombocytopenia > 7 days (or associated with bleeding or requiring more than 1 platelet transfusion), ANC < 500/mL > 7 days despite growth factors, or any thromboembolic event. Results: 18 pts (13M, 5F), med age 64 y (range, 42-80 y) were enrolled. 3 pts are ineval for DLT evaluation: one withdrew consent before starting treatment, 1 withdrew consent after a single dose, and 1 died of rapid disease progression after 1 dose. There was 1 DLT at DL1 and 2 DLTs at DL3 (Table). Adverse effects that did not meet DLT criteria: hypokalemia, hypertriglyceridemia, vomiting, urinary tract infection, skin infection, nausea, hypoxia, hyponatremia, diarrhea, and hyperglycemia (each occurring in one pt). There are 5 partial responses, 4 stable disease, 3 progressive disease, 2 not adequately assessed, and 4 still on active treatment. Conclusions: The combination of weekly intravenous TEM plus oral LEN is well-tolerated in a heavily pretreated group of pts with rel/ref lymphomas. The recommended phase II doses are TEM 25mg weekly plus LEN 20mg (D1-D21, q28d).

Demographics of patients wt and mut Rb1.

Demographics of patients with wt and mut TP53.