Neoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors.

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD and neoadjuvant therapies, co-occurring with other tumor-reactive T cells, particularly terminally exhausted CD8+ T cells (Tex). TME-wide interferon signaling correlates with cancer cells upregulating MHC class II and co-inhibitory ligands, potentially driving Treg and Tex fates. Depleting eTregs in HRD mouse models, with or without PARP inhibition, significantly suppresses tumor growth without observable toxicities, underscoring the potential of eTreg-focused therapeutics for HGSOC and other HRD-related tumors.

Tissue-resident memory and circulating T cells are early responders to pre-surgical cancer immunotherapy.

Neoadjuvant immune checkpoint blockade has shown promising clinical activity. Here, we characterized early kinetics in tumor-infiltrating and circulating immune cells in oral cancer patients treated with neoadjuvant anti-PD-1 or anti-PD-1/CTLA-4 in a clinical trial (NCT02919683). Tumor-infiltrating CD8 T cells that clonally expanded during immunotherapy expressed elevated tissue-resident memory and cytotoxicity programs, which were already active prior to therapy, supporting the capacity for rapid response. Systematic target discovery revealed that treatment-expanded tumor T cell clones in responding patients recognized several self-antigens, including the cancer-specific antigen MAGEA1. Treatment also induced a systemic immune response characterized by expansion of activated T cells enriched for tumor-infiltrating T cell clonotypes, including both pre-existing and emergent clonotypes undetectable prior to therapy. The frequency of activated blood CD8 T cells, notably pre-treatment PD-1-positive KLRG1-negative T cells, was strongly associated with intra-tumoral pathological response. These results demonstrate how neoadjuvant checkpoint blockade induces local and systemic tumor immunity.

Current and future cancer staging after neoadjuvant treatment for solid tumors.

Until recently, cancer registries have only collected cancer clinical stage at diagnosis, before any therapy, and pathological stage after surgical resection, provided no treatment has been given before the surgery, but they have not collected stage data after neoadjuvant therapy (NAT). Because NAT is increasingly being used to treat a variety of tumors, it has become important to make the distinction between both the clinical and the pathological assessment without NAT and the assessment after NAT to avoid any misunderstanding of the significance of the clinical and pathological findings. It also is important that cancer registries collect data after NAT to assess response and effectiveness of this treatment approach on a population basis. The prefix y is used to denote stage after NAT. Currently, cancer registries of the American College of Surgeons' Commission on Cancer only partially collect y stage data, and data on the clinical response to NAT (yc or posttherapy clinical information) are not collected or recorded in a standardized fashion. In addition to NAT, nonoperative management after radiation and chemotherapy is being used with increasing frequency in rectal cancer and may be expanded to other treatment sites. Using examples from breast, rectal, and esophageal cancers, the pathological and imaging changes seen after NAT are reviewed to demonstrate appropriate staging.

Treatment of muscle-invasive and advanced bladder cancer in 2020.

Bladder cancer accounts for nearly 170,000 deaths worldwide annually. For over 4 decades, the systemic management of muscle-invasive and advanced bladder cancer has primarily consisted of platinum-based chemotherapy. Over the past 10 years, innovations in sequencing technologies have led to rapid genomic characterization of bladder cancer, deepening our understanding of bladder cancer pathogenesis and exposing potential therapeutic vulnerabilities. On the basis of its high mutational burden, immune checkpoint inhibitors were investigated in advanced bladder cancer, revealing durable responses in a subset of patients. These agents are now approved for several indications and highlight the changing treatment landscape of advanced bladder cancer. In addition, commonly expressed molecular targets were leveraged to develop targeted therapies, such as fibroblast growth factor receptor inhibitors and antibody-drug conjugates. The molecular characterization of bladder cancer and the development of novel therapies also have stimulated investigations into optimizing treatment approaches for muscle-invasive bladder cancer. Herein, the authors review the history of muscle-invasive and advanced bladder cancer management, highlight the important molecular characteristics of bladder cancer, describe the major advances in treatment, and offer future directions for therapeutic development.

Evolving standards of care and new challenges in the management of HER2-positive breast cancer.

The management of human epidermal growth factor receptor (HER2)-positive breast cancer (BC) has rapidly evolved over the last 20 years. Major advances have led to US Food and Drug Administration approval of 7 HER2-targeted therapies for the treatment of early-stage and/or advanced-stage disease. Although oncologic outcomes continue to improve, most patients with advanced HER2-positive BC ultimately die of their disease because of primary or acquired resistance to therapy, and patients with HER2-positive early BC who have residual invasive disease after preoperative systemic therapy are at a higher risk of distant recurrence and death. The concept of treatment de-escalation and escalation is increasingly important to optimally tailor therapy for patients with HER2-positive BC and is a major focus of the current review. Research efforts in this regard are discussed as well as updates regarding the evolving standard of care in the (neo)adjuvant and metastatic settings, including the use of novel combination therapies. The authors also briefly discuss ongoing challenges in the management of HER2-positive BC (eg, intrinsic vs acquired drug resistance, the identification of predictive biomarkers, the integration of imaging techniques to guide clinical practice), and the treatment of HER2-positive brain metastases. Research aimed at superseding these challenges will be imperative to ensure continued progress in the management of HER2-positive BC going forward.

Pharmacological modulation of RB1 activity mitigates resistance to neoadjuvant chemotherapy in locally advanced rectal cancer.

Resistance to neoadjuvant chemotherapy leads to poor prognosis of locally advanced rectal cancer (LARC), representing an unmet clinical need that demands further exploration of therapeutic strategies to improve clinical outcomes. Here, we identified a noncanonical role of RB1 for modulating chromatin activity that contributes to oxaliplatin resistance in colorectal cancer (CRC). We demonstrate that oxaliplatin induces RB1 phosphorylation, which is associated with the resistance to neoadjuvant oxaliplatin-based chemotherapy in LARC. Inhibition of RB1 phosphorylation by CDK4/6 inhibitor results in vulnerability to oxaliplatin in both intrinsic and acquired chemoresistant CRC. Mechanistically, we show that RB1 modulates chromatin activity through the TEAD4/HDAC1 complex to epigenetically suppress the expression of DNA repair genes. Antagonizing RB1 phosphorylation through CDK4/6 inhibition enforces RB1/TEAD4/HDAC1 repressor activity, leading to DNA repair defects, thus sensitizing oxaliplatin treatment in LARC. Our study identifies a RB1 function in regulating chromatin activity through TEAD4/HDAC1. It also provides the combination of CDK4/6 inhibitor with oxaliplatin as a potential synthetic lethality strategy to mitigate oxaliplatin resistance in LARC, whereby phosphorylated RB1/TEAD4 can serve as potential biomarkers to guide the patient stratification.

Emerging concepts in PD-1 checkpoint biology.

The PD-1 pathway is a cornerstone in immune regulation. While the PD-1 pathway has received considerable attention for its role in contributing to the maintenance of T cell exhaustion in chronic infection and cancer, the PD-1 pathway plays diverse roles in regulating host immunity beyond T cell exhaustion. Here, we discuss emerging concepts in the PD-1 pathway, including (1) the impact of PD-1 inhibitors on diverse T cell differentiation states including effector and memory T cell development during acute infection, as well as T cell exhaustion during chronic infection and cancer, (2) the role of PD-1 in regulating Treg cells, NK cells, and ILCs, and (3) the functions of PD-L1/B7-1 and PD-L2/RGMb/neogenin interactions. We then discuss the emerging use of neoadjuvant PD-1 blockade in the treatment of early-stage cancers and how the timing of PD-1 blockade may improve clinical outcomes. The diverse binding partners of PD-1 and its associated ligands, broad expression patterns of the receptors and ligands, differential impact of PD-1 modulation on cells depending on location and state of differentiation, and timing of PD-1 blockade add additional layers of complexity to the PD-1 pathway, and are important considerations for improving the efficacy and safety of PD-1 pathway therapeutics.

Clinicopathologic and molecular correlates to neoadjuvant chemotherapy-induced pathologic response in breast angiosarcoma.

Both primary and secondary breast angiosarcoma (AS) are characterized by multifocal presentation and aggressive behavior. Despite multimodality therapy, local and distant relapse rates remain high. Therefore, neoadjuvant chemotherapy (NACT) is employed to improve the R0 resection rates and survival, but its benefits remain controversial. Herein, we investigate pathologic and molecular correlates to NACT-induced histologic response in a group of 29 breast AS, 4 primary and 25 radiation-associated (RA). The two NACT regimens applied were anthracycline- and non-anthracycline-based. The pathologic response grade was defined as: I: ≤ 50%, II: 51%-90%, III: 91%-99%, and IV: 100%. An additional 45 primary AS and 102 RA-AS treated by surgery alone were included for survival comparison. The genomic landscape was analyzed in a subset of cases and compared to a cohort of AS without NACT on a paired tumor-normal targeted DNA NGS platform. All patients were females, with a median age of 31 years in primary AS and 68 years in RA-AS. All surgical margins were negative in NACT group. The NACT response was evenly divided between poor (Grades I-II; n = 15) and good responders (Grades III-IV; n = 14). Mitotic count >10/mm2 was the only factor inversely associated with pathologic response. By targeted NGS, all 10 post-NACT RA-AS demonstrated MYC amplification, while both primary AS harbored KDR mutations. TMB or other genomic alterations did not correlate with pathologic response. All four patients with Grade IV response remained free of disease. The good responders had a significantly better disease-specific survival (p = 0.04). There was no survival difference with NACT status or the NACT regimens applied. However, NACT patients with MYC-amplified tumors showed better disease-free survival (p = 0.04) compared to MYC-amplified patients without NACT. The overall survival of NACT group correlated with size >10 cm (p = 0.02), pathologic response (p = 0.04), and multifocality (p = 0.01) by univariate, while only size >10 cm (p = 0.03) remained significant by multivariate analysis.

Revolutionizing the battle against locally advanced breast cancer: A comprehensive insight into neoadjuvant radiotherapy.

Breast cancer (BC) constitutes one of the most pervasive malignancies affecting the female population. Despite progressive improvements in diagnostic and therapeutic technologies, leading to an increased detection of early stage BCs, locally advanced breast cancer (LABC) persists as a significant clinical challenge. Owing to its poor overall survival (OS) rate, elevated recurrence rate, and high potential for distant metastasis, LABC prominently impacts the comprehensive efficacy of BC treatments. Radiotherapy, encompassing preoperative, intraoperative, and postoperative modalities, is acknowledged as an effective strategy for mitigating BC metastasis and enhancing survival rates among patients. Nevertheless, the domain of preoperative neoadjuvant radiotherapy (NART) remains conspicuously underexplored in clinical studies. Available research suggests that NART can induce tumor volume reduction, provoke fibrotic changes in tumor and adjacent normal tissues, thereby mitigating intraoperative cancer propagation and enhancing the quality of life for LABC patients. This manuscript seeks to provide a review of contemporary research pertaining to LABC and its preoperative radiotherapy.

TBCRC 039: a phase II study of preoperative ruxolitinib with or without paclitaxel for triple-negative inflammatory breast cancer.

BACKGROUND: Patients with inflammatory breast cancer (IBC) have overall poor clinical outcomes, with triple-negative IBC (TN-IBC) being associated with the worst survival, warranting the investigation of novel therapies. Preclinical studies implied that ruxolitinib (RUX), a JAK1/2 inhibitor, may be an effective therapy for TN-IBC. METHODS: We conducted a randomized phase II study with nested window-of-opportunity in TN-IBC. Treatment-naïve patients received a 7-day run-in of RUX alone or RUX plus paclitaxel (PAC). After the run-in, those who received RUX alone proceeded to neoadjuvant therapy with either RUX + PAC or PAC alone for 12 weeks; those who had received RUX + PAC continued treatment for 12 weeks. All patients subsequently received 4 cycles of doxorubicin plus cyclophosphamide prior to surgery. Research tumor biopsies were performed at baseline (pre-run-in) and after run-in therapy. Tumors were evaluated for phosphorylated STAT3 (pSTAT3) by immunostaining, and a subset was also analyzed by RNA-seq. The primary endpoint was the percent of pSTAT3-positive pre-run-in tumors that became pSTAT3-negative. Secondary endpoints included pathologic complete response (pCR). RESULTS: Overall, 23 patients were enrolled, of whom 21 completed preoperative therapy. Two patients achieved pCR (8.7%). pSTAT3 and IL-6/JAK/STAT3 signaling decreased in post-run-in biopsies of RUX-treated samples, while sustained treatment with RUX + PAC upregulated IL-6/JAK/STAT3 signaling compared to RUX alone. Both treatments decreased GZMB+ T cells implying immune suppression. RUX alone effectively inhibited JAK/STAT3 signaling but its combination with PAC led to incomplete inhibition. The immune suppressive effects of RUX alone and in combination may negate its growth inhibitory effects on cancer cells. CONCLUSION: In summary, the use of RUX in TN-IBC was associated with a decrease in pSTAT3 levels despite lack of clinical benefit. Cancer cell-specific-targeting of JAK2/STAT3 or combinations with immunotherapy may be required for further evaluation of JAK2/STAT3 signaling as a cancer therapeutic target. TRIAL REGISTRATION: www. CLINICALTRIALS: gov , NCT02876302. Registered 23 August 2016.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer.

BACKGROUND: Pathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30-40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60-70% show residual disease (RD). The role of the tumor microenvironment in NAC response in patients with TNBC remains unclear. In this study, we developed a machine learning-based two-step pipeline to distinguish between various histological components in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of TNBC tissue biopsies and to identify histological features that can predict NAC response. METHODS: H&E-stained WSIs of treatment-naïve biopsies from 85 patients (51 with pCR and 34 with RD) of the model development cohort and 79 patients (41 with pCR and 38 with RD) of the validation cohort were separated through a stratified eightfold cross-validation strategy for the first step and leave-one-out cross-validation strategy for the second step. A tile-level histology label prediction pipeline and four machine-learning classifiers were used to analyze 468,043 tiles of WSIs. The best-trained classifier used 55 texture features from each tile to produce a probability profile during testing. The predicted histology classes were used to generate a histology classification map of the spatial distributions of different tissue regions. A patient-level NAC response prediction pipeline was trained with features derived from paired histology classification maps. The top graph-based features capturing the relevant spatial information across the different histological classes were provided to the radial basis function kernel support vector machine (rbfSVM) classifier for NAC treatment response prediction. RESULTS: The tile-level prediction pipeline achieved 86.72% accuracy for histology class classification, while the patient-level pipeline achieved 83.53% NAC response (pCR vs. RD) prediction accuracy of the model development cohort. The model was validated with an independent cohort with tile histology validation accuracy of 83.59% and NAC prediction accuracy of 81.01%. The histological class pairs with the strongest NAC response predictive ability were tumor and tumor tumor-infiltrating lymphocytes for pCR and microvessel density and polyploid giant cancer cells for RD. CONCLUSION: Our machine learning pipeline can robustly identify clinically relevant histological classes that predict NAC response in TNBC patients and may help guide patient selection for NAC treatment.

Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer.

BACKGROUND: This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients. METHODS: A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre­therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines. RESULTS: Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels. CONCLUSION: Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.

HER2-low and tumor infiltrating lymphocytes in triple-negative breast cancer: Are they connected?

Most patients with triple-negative breast cancer (TNBC) are not candidates for targeted therapy, leaving chemotherapy as the primary treatment option. Recently, immunotherapy has demonstrated promising results in TNBC, due to its immunogenicity. In addition, a novel antibody-drug conjugate, namely, trastuzumab-deruxtecan, has shown effectiveness in TNBC patients with low-HER2 expression (HER2-low). These novel treatment options raise the question about the potential association between the density of stromal tumor-infiltrating lymphocytes (sTILs) and the level of HER2 expression. We aimed to evaluate the association between the level of HER2 expression (HER2-low versus HER2-0) and density of sTILs in TNBC patients, and how they impact the response to neoadjuvant chemotherapy (NAC). This was a retrospective multicenter study including all TNBC patients diagnosed between 2018 and 2022. Central pathology review included sTILs percentages and level of HER2 expression. Tumors were reclassified as either HER2-0 (HER2 IHC 0) or HER2-low (IHC 1 + or 2 + with negative reflex test). Various clinicopathologic characteristics, including sTILs density, and response to NAC were compared between HER2-0 and HER2-low cases. In total, 753 TNBC patients were included in this study, of which 292 patients received NAC. Interobserver agreement between the original pathology report and central review was moderate (77% had the same IHC status after reclassification in either HER2-0 or HER2-low; k = 0.45). HER2-low TNBC represented about one third (36%) of the tumors. No significant difference in sTILs density or complete pathologic response rate was found between HER2-0 and HER2-low cases (p = 0.476 and p = 0.339, respectively). The density of sTILs (≥ 10% sTILs vs. < 10%) was independently associated with achieving a pCR (p = 0.011). In conclusion, no significant association was found between HER2-low status and density of sTILs nor response to NAC. Nonetheless, sTILs could be an independent biomarker for predicting NAC response in TNBC patients.

Micrometastases in axillary lymph nodes in breast cancer, post-neoadjuvant systemic therapy.

INTRODUCTION: The significance of minimal residual axillary disease, specifically micrometastases, following neoadjuvant systemic therapy (NST) remains largely unexplored. Our study aimed to elucidate the prognostic implications of micrometastases in axillary and sentinel lymph nodes following NST. METHODS: This retrospective study analyzed primary breast cancer patients who underwent surgery after NST from September 2006 through February 2018. All patients received axillary lymph node dissection (ALND), either with or without sentinel lymph node biopsy. Recurrence-free survival (RFS)-associated variables were identified using a multivariate Cox proportional hazard model. RESULTS: Of the 978 patients examined, 438 (44.8%) exhibited no pathologic lymph node involvement (ypN0) after NST, while 89 (9.1%) had micrometastases (ypN1mi) and 451 (46.7%) had macrometastases (ypN+). Notably, 51.1% of the patients with sentinel lymph node micrometastases (SLNmi) had additional metastases, nearly triple that of SLN-negative patients (P < 0.001), and 29.8% of SLNmi patients were upstaged with the ALND. Although ypN1mi was not associated with RFS in patients post-NST (HR, 1.02; 95% CI, 0.42-2.49; P = 0.958), SLNmi patients experienced significantly worse RFS compared to SLN-negative patients (hazard ratio [HR], 2.23; 95% confidence intervals [CI], 1.12-4.46; P = 0.023). Additional metastases in SLNmi were more prevalent in patients with larger residual breast disease greater than 20 mm, HR-positive/HER2-negative subtype, and low Ki-67 LI (< 14%). CONCLUSIONS: SLNmi is a negative prognostic factor significantly associated with additional non-SLN metastases, while ypN1mi does not influence the prognosis compared to ypN0. Hence, additional ALND may be warranted to confirm axillary nodal status in patients with SLNmi.

MRI-based tumor shrinkage patterns after early neoadjuvant therapy in breast cancer: correlation with molecular subtypes and pathological response after therapy.

BACKGROUND: MRI-based tumor shrinkage patterns (TSP) after neoadjuvant therapy (NAT) have been associated with pathological response. However, the understanding of TSP after early NAT remains limited. We aimed to analyze the relationship between TSP after early NAT and pathological response after therapy in different molecular subtypes. METHODS: We prospectively enrolled participants with invasive ductal breast cancers who received NAT and performed pretreatment DCE-MRI from September 2020 to August 2022. Early-stage MRIs were performed after the first (1st-MRI) and/or second (2nd-MRI) cycle of NAT. Tumor shrinkage patterns were categorized into four groups: concentric shrinkage, diffuse decrease (DD), decrease of intensity only (DIO), and stable disease (SD). Logistic regression analysis was performed to identify independent variables associated with pathologic complete response (pCR), and stratified analysis according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. RESULTS: 344 participants (mean age: 50 years, 113/345 [33%] pCR) with 345 tumors (1 bilateral) had evaluable 1st-MRI or 2nd-MRI to comprise the primary analysis cohort, of which 244 participants with 245 tumors had evaluable 1st-MRI (82/245 [33%] pCR) and 206 participants with 207 tumors had evaluable 2nd-MRI (69/207 [33%] pCR) to comprise the 1st- and 2nd-timepoint subgroup analysis cohorts, respectively. In the primary analysis, multivariate analysis showed that early DD pattern (OR = 12.08; 95% CI 3.34-43.75; p < 0.001) predicted pCR independently of the change in tumor size (OR = 1.37; 95% CI 0.94-2.01; p = 0.106) in HR+/HER2- subtype, and the change in tumor size was a strong pCR predictor in HER2+ (OR = 1.61; 95% CI 1.22-2.13; p = 0.001) and triple-negative breast cancer (TNBC, OR = 1.61; 95% CI 1.22-2.11; p = 0.001). Compared with the change in tumor size, the SD pattern achieved a higher negative predictive value in HER2+ and TNBC. The statistical significance of complete 1st-timepoint subgroup analysis was consistent with the primary analysis. CONCLUSION: The diffuse decrease pattern in HR+/HER2- subtype and stable disease in HER2+ and TNBC after early NAT could serve as additional straightforward and comprehensible indicators of treatment response. TRIAL REGISTRATION: Trial registration at https://www.chictr.org.cn/ . REGISTRATION NUMBER: ChiCTR2000038578, registered September 24, 2020.

Metabolic adaptation towards glycolysis supports resistance to neoadjuvant chemotherapy in early triple negative breast cancers.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is the standard of care for patients with early-stage triple negative breast cancers (TNBC). However, more than half of TNBC patients do not achieve a pathological complete response (pCR) after NAC, and residual cancer burden (RCB) is associated with dismal long-term prognosis. Understanding the mechanisms underlying differential treatment outcomes is therefore critical to limit RCB and improve NAC efficiency. METHODS: Human TNBC cell lines and patient-derived organoids were used in combination with real-time metabolic assays to evaluate the effect of NAC (paclitaxel and epirubicin) on tumor cell metabolism, in particular glycolysis. Diagnostic biopsies (pre-NAC) from patients with early TNBC were analyzed by bulk RNA-sequencing to evaluate the predictive value of a glycolysis-related gene signature. RESULTS: Paclitaxel induced a consistent metabolic switch to glycolysis, correlated with a reduced mitochondrial oxidative metabolism, in TNBC cells. In pre-NAC diagnostic biopsies from TNBC patients, glycolysis was found to be upregulated in non-responders. Furthermore, glycolysis inhibition greatly improved response to NAC in TNBC organoid models. CONCLUSIONS: Our study pinpoints a metabolic adaptation to glycolysis as a mechanism driving resistance to NAC in TNBC. Our data pave the way for the use of glycolysis-related genes as predictive biomarkers for NAC response, as well as the development of inhibitors to overcome this glycolysis-driven resistance to NAC in human TNBC patients.

Promoter profiles in plasma CfDNA exhibits a potential utility of predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients.

BACKGROUND: Gene expression profiles in breast tissue biopsies contain information related to chemotherapy efficacy. The promoter profiles in cell-free DNA (cfDNA) carrying gene expression information of the original tissues may be used to predict the response to neoadjuvant chemotherapy in breast cancer as a non-invasive biomarker. In this study, the feasibility of the promoter profiles in plasma cfDNA was evaluated as a novel clinical model for noninvasively predicting the efficacy of neoadjuvant chemotherapy in breast cancer. METHOD: First of all, global chromatin (5 Mb windows), sub-compartments and promoter profiles in plasma cfDNA samples from 94 patients with breast cancer before neoadjuvant chemotherapy (pCR = 31 vs. non-pCR = 63) were analyzed, and then classifiers were developed for predicting the efficacy of neoadjuvant chemotherapy in breast cancer. Further, the promoter profile changes in sequential cfDNA samples from 30 patients (pCR = 8 vs. non-pCR = 22) during neoadjuvant chemotherapy were analyzed to explore the potential benefits of cfDNA promoter profile changes as a novel potential biomarker for predicting the treatment efficacy. RESULTS: The results showed significantly distinct promoter profile in plasma cfDNA of pCR patients compared with non-pCR patients before neoadjuvant chemotherapy. The classifier based on promoter profiles in a Random Forest model produced the largest area under the curve of 0.980 (95% CI: 0.978-0.983). After neoadjuvant chemotherapy, 332 genes with significantly differential promoter profile changes in sequential cfDNA samples of pCR patients was observed, compared with non-pCR patients, and their functions were closely related to treatment response. CONCLUSION: These results suggest that promoter profiles in plasma cfDNA may be a powerful, non-invasive tool for predicting the efficacy of neoadjuvant chemotherapy breast cancer patients before treatment, and the on-treatment cfDNA promoter profiles have potential benefits for predicting the treatment efficacy.

A prospective study of HER3 expression pre and post neoadjuvant therapy of different breast cancer subtypes: implications for HER3 imaging therapy guidance.

PURPOSE: HER3, a member of the EGFR receptor family, plays a central role in driving oncogenic cell proliferation in breast cancer. Novel HER3 therapeutics are showing promising results while recently developed HER3 PET imaging modalities aid in predicting and assessing early treatment response. However, baseline HER3 expression, as well as changes in expression while on neoadjuvant therapy, have not been well-characterized. We conducted a prospective clinical study, pre- and post-neoadjuvant/systemic therapy, in patients with newly diagnosed breast cancer to determine HER3 expression, and to identify possible resistance mechanisms maintained through the HER3 receptor. EXPERIMENTAL DESIGN: The study was conducted between May 25, 2018 and October 12, 2019. Thirty-four patients with newly diagnosed breast cancer of any subtype (ER ± , PR ± , HER2 ±) were enrolled in the study. Two core biopsy specimens were obtained from each patient at the time of diagnosis. Four patients underwent a second research biopsy following initiation of neoadjuvant/systemic therapy or systemic therapy which we define as neoadjuvant therapy. Molecular characterization of HER3 and downstream signaling nodes of the PI3K/AKT and MAPK pathways pre- and post-initiation of therapy was performed. Transcriptional validation of finings was performed in an external dataset (GSE122630). RESULTS: Variable baseline HER3 expression was found in newly diagnosed breast cancer and correlated positively with pAKT across subtypes (r = 0.45). In patients receiving neoadjuvant/systemic therapy, changes in HER3 expression were variable. In a hormone receptor-positive (ER +/PR +/HER2-) patient, there was a statistically significant increase in HER3 expression post neoadjuvant therapy, while there was no significant change in HER3 expression in a ER +/PR +/HER2+ patient. However, both of these patients showed increased downstream signaling in the PI3K/AKT pathway. One subject with ER +/PR -/HER2- breast cancer and another subject with ER +/PR +/HER2 + breast cancer showed decreased HER3 expression. Transcriptomic findings, revealed an immune suppressive environment in patients with decreased HER3 expression post therapy. CONCLUSION: This study demonstrates variable HER3 expression across breast cancer subtypes. HER3 expression can be assessed early, post-neoadjuvant therapy, providing valuable insight into cancer biology and potentially serving as a prognostic biomarker. Clinical translation of neoadjuvant therapy assessment can be achieved using HER3 PET imaging, offering real-time information on tumor biology and guiding personalized treatment for breast cancer patients.

Outcomes of sentinel node biopsy according to MRI response in an association with the subtypes in cN1-3 breast cancer after neoadjuvant systemic therapy, multicenter cohort study.

BACKGROUND: This study investigated the feasibility of sentinel lymph node biopsy (SLNB) after neoadjuvant systemic therapy (NAST) in patients with initially high nodal burden. METHODS: In the multicenter retrospective cohort, 388 individuals with cN1-3 breast cancer who underwent NAST and had SLNB followed by completion axillary lymph node dissection were included. In an external validation cohort, 267 patients with HER2+ or triple-negative breast cancer (TNBC) meeting similar inclusion criteria were included. Primary outcome was the false-negative rates (FNRs) of SLNB according to the MRI response and subtypes. We defined complete MRI responders as patients who experienced disappearance of suspicious features in the breast and axilla after NAST. RESULTS: In the multicenter retrospective cohort, 130 (33.5%) of 388 patients were of cN2-3, and 55 (14.2%) of 388 patients showed complete MRI responses. In hormone receptor-positive HER2- (n = 207), complete and non-complete responders had a high FNRs (31.3% [95% CI 8.6-54.0] and 20.9% [95% CI 14.1-27.6], respectively). However, in HER2+ or TNBC (n = 181), the FNR of complete MRI responders was 0% (95% CI 0-0), whereas that of non-complete responders was 33.3% (95% CI 20.8-45.9). When we validated our findings in the external cohort with HER2+ or TNBC (n = 267), of which 34.2% were cN2-3, the FNRs of complete were 7.1% (95% CI 0-16.7). CONCLUSIONS: Our findings suggest that SLNB can be a reliable option for nodal status evaluation in selected patients who have responded well to NAST, especially in HER2+ and TNBC patients who show a complete MRI response.

Factors associated with engraftment success of patient-derived xenografts of breast cancer.

BACKGROUND: Patient-derived xenograft (PDX) models serve as a valuable tool for the preclinical evaluation of novel therapies. They closely replicate the genetic, phenotypic, and histopathological characteristics of primary breast tumors. Despite their promise, the rate of successful PDX engraftment is various in the literature. This study aimed to identify the key factors associated with successful PDX engraftment of primary breast cancer. METHODS: We integrated clinicopathological data with morphological attributes quantified using a trained artificial intelligence (AI) model to identify the principal factors affecting PDX engraftment. RESULTS: Multivariate logistic regression analyses demonstrated that several factors, including a high Ki-67 labeling index (Ki-67LI) (p < 0.001), younger age at diagnosis (p = 0.032), post neoadjuvant chemotherapy (NAC) (p = 0.006), higher histologic grade (p = 0.039), larger tumor size (p = 0.029), and AI-assessed higher intratumoral necrosis (p = 0.027) and intratumoral invasive carcinoma (p = 0.040) proportions, were significant factors for successful PDX engraftment (area under the curve [AUC] 0.905). In the NAC group, a higher Ki-67LI (p < 0.001), lower Miller-Payne grade (p < 0.001), and reduced proportion of intratumoral normal breast glands as assessed by AI (p = 0.06) collectively provided excellent prediction accuracy for successful PDX engraftment (AUC 0.89). CONCLUSIONS: We found that high Ki-67LI, younger age, post-NAC status, higher histologic grade, larger tumor size, and specific morphological attributes were significant factors for predicting successful PDX engraftment of primary breast cancer.