Biomedical subjects

William Sikov

Publications and source records attributed to William Sikov.

4 recordsLinked to original sources

PubMed2026

Molecular evaluation of residual disease following neoadjuvant chemotherapy in triple-negative breast cancer CALGB 40603 (Alliance).

BACKGROUNDDespite therapeutic advances in early-stage triple-negative breast cancer (TNBC), residual disease (RD) following neoadjuvant therapy remains a key predictor of a worse prognosis and obstacle to improving patient outcomes.METHODSTo better characterize RD and identify survival-associated features, we performed comprehensive transcriptomic profiling of 340 pretreatment stage II/III TNBCs and 70 matched posttreatment RD samples from the randomized CALGB 40603 (Alliance) phase II clinical trial. To explore preclinical treatment strategies for RD, patient-derived xenograft (PDX) mouse models mimicking RD were treated with antibody-drug conjugates (ADCs).RESULTSOur study shows prognostic genomic features measured pretreatment may differ from prognostic features measured posttreatment from RD specimens. Patients with a genomic PAM50 subtype of basal-like in RD specimens had a poor survival outcome, and their matching pretreatment tumors were characterized by elevated chromosomal amplifications of oncogenic drivers and significantly reduced B and T cell expression features. Paired analyses of basal-like RD and matched pretreatment tumors revealed further lymphocyte depletion in RD, along with lower expression of MHC class I and interferon signaling, indicating an immune-cold RD microenvironment. Treatment of a basal-like and conventional chemotherapy-resistant PDX model, resembling basal-like RD, with sacituzumab govitecan or trastuzumab deruxtecan produced a marked antitumor response.CONCLUSIONRD biology differs from pretreatment tumors, with basal-like subtype RD following neoadjuvant chemotherapy being immune cold and associated with poor survival. Preclinical modeling suggests this high-risk group may benefit from adjuvant ADC therapy.TRIAL REGISTRATIONClinicalTrials.gov NCT00861705.FUNDINGNIH NCI U10CA180821 (Alliance for Clinical Trials in Oncology), NCI U24CA176171 (Alliance for Clinical Trials in Oncology), NCI UG1CA233373 (Alliance for Clinical Trials in Oncology), NCI Breast SPORE program P50-CA058223; Susan G. Komen SAC-160074; Breast Cancer Research Foundation BCRF-23-127; NIH NCI R01-CA229409; UNC LCCC Triple Negative Breast Cancer Center.

Humans↗

PubMed2025

Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast Cancer.

Deep learning models applied to digital histology can predict gene expression signatures (GES) and offer a low-cost, rapidly available alternative to molecular testing at the time of diagnosis. We optimized transformer-based models to infer GES results and applied this approach to pre-treatment H&E-stained biopsies from 1,940 breast cancer patients treated with neoadjuvant chemotherapy in clinical trial and real-world cohorts. The most predictive histology-derived GES for pathologic complete response (pCR) in the I-SPY2 trial was validated in four external cohorts: CALGB 40601, CALGB 40603, a trial of durvalumab plus CT, and standard-of-care CT-treated patients from the University of Chicago. Among HER2-negative patients, a transformer-based model trained using a signature composed of estrogen-regulated genes, proliferation, apoptosis, and interferon response genes predicted pCR with an AUC of 0.794, outperforming models based on clinical features alone (AUC 0.704, p = 0.001), pathologist TIL assessment, and a model trained directly to predict response from I-SPY2 cases. Tertiles of this signature stratify patients into clinically relevant groups with increasing likelihood of complete response, with pCR rates ≥50% in the top tertile regardless of treatment or hormone receptor status. Additional transformer-based signature models predicted response to specific therapies (but not chemotherapy alone), including a HER2 signaling signature in IO-treated patients, and a claudin-low signature in bevacizumab treated patients. In HER2- cohorts with available gene expression data and histology, models trained on expression data performed similarly to digital histology predictions, but the combination of gene expression and histology outperformed histology alone. These findings suggest that histology-based GES provides additive information to RNA sequencing data and can inform precision treatment selection across breast cancer subtypes.

Journal Article↗

PubMed2005

Weekly paclitaxel improves pathologic complete remission in operable breast cancer when compared with paclitaxel once every 3 weeks.

PURPOSE: To determine the impact a change in schedule of paclitaxel administration from once every 3 weeks to frequent administration would have on the pathologic complete response (pCR) rate in the breast and lymph nodes for patients with invasive breast cancer treated with primary systemic chemotherapy (PST). PATIENTS AND METHODS: Patients with clinical stage I-IIIA breast cancer were randomly assigned to receive PST of paclitaxel doses administered either weekly (for a total of 12 doses of paclitaxel) or once every 3 weeks (four cycles), followed by four cycles of fluorouracil/doxorubicin/cyclophosphamide (FAC) in standard doses every 3 weeks. Two different doses of paclitaxel were used based on lymph node status defined by ultrasound and fine needle aspiration. Clinical response and extent of residual disease in the breast and lymph nodes was assessed after completion of all chemotherapy. RESULTS: A total of 258 patients were randomly assigned to receive doses of paclitaxel administered either weekly or once every 3 weeks, followed by FAC. Of these 258 patients, 110 patients had histologic lymph node involvement and 148 patients had clinical N0 disease. Weekly paclitaxel followed by FAC was administered to 127 patients and once-every-3-weeks paclitaxel followed by FAC was administered to 131 patients. Clinical response to treatment was similar between groups (P = .25). Patients receiving weekly paclitaxel had a higher pCR rate (28.2%) than patients treated with once-every-3-weeks paclitaxel (15.7%; P = .02), with improved breast conservation rates (P = .05). CONCLUSION: The change in schedule of paclitaxel from once every 3 weeks to a more frequent administration significantly improved the ability to eradicate invasive cancer in the breast and lymph nodes.

Adult↗

PubMed2002

A phase I study of a weekly schedule of paclitaxel and carboplatin in patients with advanced carcinoma.

BACKGROUND: We conducted a Phase I study of weekly paclitaxel (P) and carboplatin (C) in patients with advanced malignancies to determine the maximum tolerated dose (MTD) of this combination. METHODS: Dose levels were escalated independently for patients with and without previous chemotherapy exposure and advanced malignancies. Both agents were administered weekly for 6 weeks followed by a 2-week break per cycle. P, escalated to tolerance starting at 135 mg/m(2) per week, and C, fixed dose at area under the curve (AUC) = 2 mg/mL/min, were administered to groups of three or six patients. Doses were modified for granulocyte counts less than 1800/microL or for neurotoxicity greater than Grade 1. MTD was defined as the highest dose level at which less than 50% of patients developed unacceptable toxicity and received more than 80% of the intended dose during the first cycle. Dose levels were escalated until these conditions were exceeded. RESULTS: Twenty-seven patients (12 patients with previous chemotherapy exposure and 15 chemotherapy-naive patients) were examined for toxicity. Dose escalation was halted due to neutropenia and/or Grade 2/3 neuropathy in both arms. The MTD was P = 135/C = 2 for patients with previous chemotherapy exposure and P = 150/C = 2 for chemotherapy-naive patients. CONCLUSIONS: The combination of P and C administered on a weekly schedule permits a two to threefold enhancement of P dose intensity with full doses of C. Phase II trials of this regimen in patients with various malignancies are being evaluated to determine efficacy and tolerance.

Adult↗