Wan, Fei

Abstract Purpose: Polatuzumab vedotin (polatuzumab) was approved for up-front treatment of diffuse large B-cell lymphoma in combination with chemoimmunotherapy (Pola-R-CHP) based on the POLARIX trial. However, when stratified by cell of origin (COO), polatuzumab seems to have greater efficacy in activated B-cell than germinal center B-cell (GCB) subtype disease. Most studies of polatuzumab used RNA expression to assess COO, whereas in routine clinical practice, the immunohistochemistry-based Hans algorithm is used. Experimental Design: To assess the impact of COO by immunohistochemistry on polatuzumab efficacy, we conducted a multicenter real-world study of adults with large B-cell lymphoma (LBCL) receiving polatuzumab from 2015 to 2024, split by receipt of polatuzumab in first-line versus relapsed/refractory settings. The primary endpoint was overall response rate (ORR) to polatuzumab-based treatment in GCB versus non-GCB relapsed/refractory LBCL. Results: Of 740 patients, 305 received polatuzumab in the first-line setting and 435 in the relapsed/refractory setting. In the relapsed/refractory cohort, the ORR in non-GCB versus GCB LBCL was 59.7% versus 36.3% [OR, 2.6; 95% confidence interval (CI), 1.77–3.84; P < 0.0001], with a complete response rate of 35.7% versus 17.7% (OR, 2.6; 95% CI, 1.66–4.02; P < 0.0001). Progression-free survival was longer for patients with non-GCB versus GCB COO (HR, 0.64; 95% CI, 0.5–0.83; P = 0.0006). In the first-line cohort, ORR, complete response rate, and progression-free survival were similar in non-GCB versus GCB LBCL, as hypothesized based on outcomes in the Pola-R-CHP arm of POLARIX, suggesting that the addition of polatuzumab overcomes the adverse risk of non-GCB COO in patients receiving R-CHOP. Conclusions: Based on these data, COO classification by the Hans algorithm is a strong predictor of polatuzumab efficacy in LBCL, informing real-world treatment decisions.

Background: Polatuzumab vedotin (Pola) is an antibody drug conjugate targeting CD79b that incorporates the microtubule disrupting monomethyl auristatin E payload. Pola was approved in 2023 for the upfront treatment of diffuse large B cell lymphoma (DLBCL) in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (polaRCHP) based on the POLARIX trial. However, the activity of pola appears to vary based on DLBCL cell of origin (COO) subtype, with greater efficacy in activated B cell (ABC) DLBCL compared to germinal center B cell (GCB) DLBCL (Russler-Germain Blood 2023). When outcomes in POLARIX are stratified by COO, polaRCHP demonstrated progression free survival (PFS) and overall survival (OS) benefits over RCHOP in patients with ABC but not GCB subtype DLBCL (PFS HR 0.34 ABC vs 1.03 GCB, OS HR 0.27 ABC vs 1.64 GCB; Morschhauser ASH 2023 and FDA data). Most prospective studies of pola used gene expression to assess COO, which is not readily clinically available. This study aims to examine if COO subtype by Hans algorithm (based on CD10, BCL6, and MUM1 expression by immunohistochemistry) is predictive of pola responses and outcomes in patients with large B cell lymphoma (LBCL). Methods: We conducted a retrospective, multicenter observational study of adults with LBCL who received pola (monotherapy or in combination) from 2015-2024 with Hans algorithm COO data and response assessment available. Patients were stratified by receipt of pola in the frontline vs relapsed/refractory (R/R) setting. The primary endpoint was overall response rate (ORR) to pola-based treatment in GCB vs non-GCB subtypes. Secondary endpoints included complete response rate (CRR), PFS, and OS. For time to event endpoints, patients responding to pola who received CAR T or stem cell transplantation prior to progression were censored at time of cellular therapy. Demographics were summarized by descriptive statistics. Comparative and survival analyses used Chi squared/Fischer exact tests and Kaplan Meier analysis. Data cutoff was July 1, 2024. Results: 718 patients were included. Median follow-up was 15 months (interquartile range [IQR] 8-32). Median age at LBCL diagnosis was 66 years (IQR 56-74); 62% were men; 69 (10%) had double hit lymphoma (DHL); 129 (18%) had underlying low grade lymphoma. Pola was used in the frontline setting in 293 (41%) patients, of whom 139 (47%) had GCB vs 154 (53%) non-GCB COO. Of the 426 patients receiving pola for R/R LBCL (including one patient receiving pola retreatment), 224 (53%) had GCB vs 202 (47%) non-GCB COO. Among patients receiving pola-based regimens in the R/R setting (GCB vs non-GCB: pola monotherapy = 7% vs 4%, pola + R = 26% vs 26%, pola + BR = 55% vs 61%, pola + other = 12% vs 9%; p = 0.44), the ORR in GCB vs non-GCB LBCL was 36% vs 61% (p < 0.001), while CRR in GCB vs non-GCB was 17% vs 36% (p < 0.001). COO remained a significant component of logistic multivariate regression models of ORR (p < 0.001) and CRR (p < 0.001) when incorporating IPI at original LBCL diagnosis, histology, DHL status, and refractory status to frontline therapy. Despite this, no significant PFS or OS differences by COO were seen, potentially due to approximately 1/4 patients being censored due to receiving subsequent cellular therapy (e.g. CAR T) prior to progression. In patients receiving frontline pola-based regimens (of which 275 [94%] included an anthracycline), ORR and CRR were similar in GCB vs non-GCB (ORR 89% vs 88% p > 0.5; CRR 76% vs 77% p > 0.5). While PFS and OS were similar between COO groups in the frontline cohort, follow-up and cohort size were limited. Conclusion: Based on this real-world evidence, COO classification by Hans algorithm is a strong predictor of the activity of pola-containing therapy in R/R LBCL, with significantly higher ORR and CRR in patients with non-GCB compared to GCB COO LBCL. This aligns with the cumulative existing evidence. ORR and CRR to pola-containing therapy in the frontline setting did not differ significantly by COO subtype, but longer follow-up of larger cohorts is needed to clarify the predictive role of COO by Hans algorithm in this setting, especially considering the PFS advantage with polaRCHP in POLARIX was not associated with significant differences in ORR or CRR. Overall, clinicians should consider factoring COO subtype into treatment decisions regarding pola-containing regimens, and studies of pola-based therapies should stratify patients and report outcomes by COO subtype.

Abstract Inherited BRCA1/2 mutations confer elevated ovarian cancer risk. Knowledge of factors that can improve ovarian cancer risk assessment in BRCA1/2 mutation carriers is important because no effective early detection for ovarian cancers exists. A cohort of 1,575 BRCA1 and 856 BRCA2 mutation carriers was used to evaluate haplotypes at ATM, BARD1, BRIP1, CTIP, MRE11, NBS1, RAD50, RAD51, and TOPBP1 in ovarian cancer risk. In BRCA1 carriers, no associations were observed with ATM, BARD1, CTIP, RAD50, RAD51, or TOPBP1. At BRIP1, an association was observed for one haplotype with a multiple testing corrected P (Pcorr) = 0.012, although no individual haplotype was significant. At MRE11, statistically significant associations were observed for one haplotype (Pcorr = 0.007). At NBS1, we observed a Pcorr = 0.024 for haplotypes. In BRCA2 carriers, no associations were observed with CTIP, NBS1, RAD50, or TOPBP1. Rare haplotypes at ATM (Pcorr = 0.044) and BARD1 (Pcorr = 0.012) were associated with ovarian cancer risk. At BRIP1, two common haplotypes were significantly associated with ovarian cancer risk (Pcorr = 0.011). At MRE11, we observed a significant haplotype association (Pcorr = 0.012), and at RAD51, one common haplotype was significantly associated with ovarian cancer risk (Pcorr = 0.026). Variants in genes that interact biologically withBRCA1 and/or BRCA2 may be associated with modified ovarian cancer risk in women who carry BRCA1/2 mutations. [Cancer Res 2009;69(14):5801–10]