Impact of Anti-HER2 Therapy Alone and With Weekly Paclitaxel on the Ovarian Reserve of Young Women With HER2-Positive Breast Cancer.

BACKGROUND: The potential gonadotoxicity of anti-HER2 agents remains largely unknown, and limited, conflicting evidence exists for taxanes. Antimüllerian hormone (AMH) is an established biomarker of ovarian reserve that may aid in quantifying anticancer treatment-induced gonadotoxicity. PATIENTS AND METHODS: The present biomarker analysis of the randomized phase III neoadjuvant NeoALTTO trial included premenopausal women aged ≤45 years at diagnosis of HER2-positive early breast cancer with available frozen serum samples at baseline (ie, before anticancer treatments), at week 2 (ie, the "biological window" of anti-HER2 therapy alone), and/or at the time of surgery (ie, after completing paclitaxel + anti-HER2 therapy, before starting adjuvant chemotherapy). RESULTS: The present analysis included 130 patients with a median age of 38 years (interquartile ratio [IQR], age 33-42 years). AMH values at the 3 time points differed significantly (P<.001). At baseline, median AMH levels were 1.29 ng/mL (IQR, 0.56-2.62 ng/mL). At week 2, a small but significant reduction in AMH levels was observed (median, 1.10 ng/mL; IQR, 0.45-2.09 ng/mL; P<.001). At surgery, a larger significant decline in AMH levels was observed (median, 0.01 ng/mL; IQR, 0.01-0.03 ng/mL; P<.001). Although the type of anti-HER2 treatment (trastuzumab and/or lapatinib) did not seem to impact the results, age and pretreatment ovarian reserve had a major influence on treatment-induced gonadotoxicity risk. CONCLUSIONS: This NeoALTTO biomarker analysis showed that anti-HER2 therapies alone had limited gonadotoxicity but that the addition of weekly paclitaxel resulted in marked AMH decline with possible negative implications for subsequent ovarian function and fertility.

Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T imaging, and histology.

PURPOSE: Relationships between diffusion-weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange? METHODS: Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity L / D0 , and clinical protocols (single diffusion encoding; maximum b-value: {1000, 1500, 2000} s/mm2 ; 5 unique gradient duration/separation pairs; SNR = { ∞ , 100, 80, 40, 20}), accounting for heterogeneity in (D0,L) and perfusion contamination. Diffusion ( D ) and kurtosis ( K ) coefficients were calculated, and relationships between (D0,L) and (D,K) were visualized. Functions mapping (D,K) to (D0,L) were computed to predict unseen (D0,L) values, tested for their ability to classify discrete cell-size contrasts, and deployed on 9.4T ex vivo MRI-histology data of fixed mouse livers RESULTS: Relationships between (D,K) and (D0,L) are complex and depend on the diffusion encoding. Functions mapping D,K to (D0,L) captures salient characteristics of D0(D,K) and L(D,K) dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three-class cell-size classification task (for SNR = 20, bmax = 1500 s/mm2 , δ = 20 ms, and Δ = 75 ms). MRI detects cell-size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes. CONCLUSION: Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible.

A Comprehensive Biomarker Analysis of Microsatellite Unstable/Mismatch Repair Deficient Colorectal Cancer Cohort Treated with Immunotherapy.

The search for immunotherapy biomarkers in Microsatellite Instability High/Deficient Mismatch Repair system (MSI-H/dMMR) metastatic colorectal cancer (mCRC) is an unmet need. Sixteen patients with mCRC and MSI-H/dMMR (determined by either immunohistochemistry or polymerase chain reaction) treated with PD-1/PD-L1 inhibitors at our institution were included. According to whether the progression-free survival with PD-1/PD-L1 inhibitors was longer than 6 months or shorter, patients were clustered into the IT-responder group (n: 9 patients) or IT-resistant group (n: 7 patients), respectively. In order to evaluate determinants of benefit with PD-1/PD-L1 inhibitors, we performed multimodal analysis including genomics (through NGS panel tumour-only with 431 genes) and the immune microenvironment (using CD3, CD8, FOXP3 and PD-L1 antibodies). The following mutations were more frequent in IT-resistant compared with IT-responder groups: B2M (4/7 versus 2/9), CTNNB1 (2/7 versus 0/9), and biallelic PTEN (3/7 versus 1/9). Biallelic ARID1A mutations were found exclusively in the IT-responder group (4/9 patients). Tumour mutational burden did not correlate with immunotherapy benefit, neither the rate of indels in homopolymeric regions. Of note, biallelic ARID1A mutated tumours had the highest immune infiltration and PD-L1 scores, contrary to tumours with CTNNB1 mutation. Immune microenvironment analysis showed higher densities of different T cell subpopulations and PD-L1 expression in IT-responders. Misdiagnosis of MSI-H/dMMR inferred by discordances between immunohistochemistry and polymerase chain reaction was only found in the IT-resistant population (3/7 patients). Biallelic ARID1A mutations and Wnt signalling activation through CTNNB1 mutation were associated with high and low T cell immune infiltrates, respectively, and deserve special attention as determinants of response to PD-1/PD-L1 inhibitors. The non-MSI-H phenotype in dMMR is associated with poor benefit to immunotherapy. Our results suggest that mechanisms of resistance to immunotherapy are multi-factorial.

Genetic evolution to tyrosine kinase inhibitory therapy in patients with EGFR-mutated non-small-cell lung cancer.

BACKGROUND: Tumour heterogeneity impacts the efficacy of metastatic cancer treatment even if actionable mutations are identified. Clinicians need to understand if assessing one lesion provides reliable information to drive a therapeutic decision in non-small-cell lung cancer (NSCLC) patients. METHODS: We analysed inter-tumour heterogeneity from five autopsied individuals with NSCLC-harbouring mutations in the epidermal growth factor receptor (EGFR), treated with EGFR tyrosine kinase inhibitors (TKIs). Through a comprehensive next-generation sequencing (NGS) oncopanel, and an EGFR panel for digital droplet PCR (ddPCR), we compared metastases within individuals, longitudinal biopsies from the same lesions and, whenever possible, the primary naive tumour. RESULTS: Analysis of 22 necropsies from five patients revealed homogeneity in pathogenic mutations and TKI-resistance mechanisms within each patient in four of them. In-depth analysis by whole-exome sequencing from patient 1 confirmed homogeneity in clonal mutations, but heterogeneity in passenger subclonal alterations. Different resistance mechanisms were detected depending on the patient and line of treatment. Three patients treated with a c-MET inhibitor in combination with TKI lost MET amplification upon progression. CONCLUSION: At a given point and under selective TKI pressure, a single metastasis biopsy in disseminated tumours from EGFR-mutated NSCLC patients could provide a reasonable assessment of actionable alterations useful for therapeutic decisions.

PI3K activation promotes resistance to eribulin in HER2-negative breast cancer.

BACKGROUND: Eribulin is a microtubule-targeting agent approved for the treatment of advanced or metastatic breast cancer (BC) previously treated with anthracycline- and taxane-based regimens. PIK3CA mutation is associated with worse response to chemotherapy in oestrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-) metastatic BC. We aimed to evaluate the role of phosphoinositide 3-kinase (PI3K)/AKT pathway mutations in eribulin resistance. METHODS: Resistance to eribulin was evaluated in HER2- BC cell lines and patient-derived tumour xenografts, and correlated with a mutation in the PI3K/AKT pathway. RESULTS: Eleven out of 23 HER2- BC xenografts treated with eribulin exhibited disease progression. No correlation with ER status was detected. Among the resistant models, 64% carried mutations in PIK3CA, PIK3R1 or AKT1, but only 17% among the sensitive xenografts (P = 0.036). We observed that eribulin treatment induced AKT phosphorylation in vitro and in patient tumours. In agreement, the addition of PI3K inhibitors reversed primary and acquired resistance to eribulin in xenograft models, regardless of the genetic alterations in PI3K/AKT pathway or ER status. Mechanistically, PI3K blockade reduced p21 levels likely enabling apoptosis, thus sensitising to eribulin treatment. CONCLUSIONS: PI3K pathway activation induces primary resistance or early adaptation to eribulin, supporting the combination of PI3K inhibitors and eribulin for the treatment of HER2- BC patients.

A CT-based Radiomics Signature Is Associated with Response to Immune Checkpoint Inhibitors in Advanced Solid Tumors.

Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue.

Tumor-Associated Microbiome: Where Do We Stand?

The study of the human microbiome in oncology is a growing and rapidly evolving field. In the past few years, there has been an exponential increase in the number of studies investigating associations of microbiome and cancer, from oncogenesis and cancer progression to resistance or sensitivity to specific anticancer therapies. The gut microbiome is now known to play a significant role in antitumor immune responses and in predicting the efficacy of immune-checkpoint inhibitors in cancer patients. Beyond the gut, the tumor-associated microbiome-microbe communities located either in the tumor or within its body compartment-seems to interact with the local microenvironment and the tumor immune contexture, ultimately impacting cancer progression and treatment outcome. However, pre-clinical research focusing on causality and mechanistic pathways as well as proof-of-concept studies are still needed to fully understand the potential clinical utility of microbiome in cancer patients. Moreover, there is a need for the standardization of methodology and the implementation of quality control across microbiome studies to allow for a better interpretation and greater comparability of the results reported between them. This review summarizes the accumulating evidence in the field and discusses the current and upcoming challenges of microbiome studies.

Early Modulation of Circulating MicroRNAs Levels in HER2-Positive Breast Cancer Patients Treated with Trastuzumab-Based Neoadjuvant Therapy.

Circulating microRNA (ct-miRNAs) are able to identify patients with differential response to HER2-targeted therapy. However, their dynamics are largely unknown. We assessed 752 miRNAs from 52 NeoALTTO patients with plasma pairs prior and two weeks after trastuzumab. Increased levels of ct-miR-148a-3p and ct-miR-374a-5p were significantly associated with pathological complete response (pCR) (p = 0.008 and 0.048, respectively). At a threshold ≥ the upper limit of the 95%CI of the mean difference, pCR resulted 45% (95%CI 24%-68%), and 44% (95%CI 22%-69%) for ct-miR-148a-3p and ct-miR-374a-5p, respectively. Notably, ct-miR-148a-3p retained its predictive value (OR 3.42, 95%CI 1.23-9.46, p = 0.018) in bivariate analysis along with estrogen receptor status. Combined information from ct-miR-148a-3p and ct-miR140-5p, which we previously reported to identify trastuzumab-responsive patients, resulted in greater predictive capability over each other, with pCR of 54% (95%CI 25%-81%) and 0% (95%CI 0%-31%) in ct-miR-148a/ct-miR-140-5p high/present and low/absent, respectively. GO and KEGG analyses showed common enriched terms between the targets of these ct-miRNAs, including cell metabolism regulation, AMPK and MAPK signaling, and HCC progression. In conclusion, early modulated ct-miR-148-3p may inform on the functional processes underlying treatment response, integrate the information from already available predictive biomarkers, and identify patients likely to respond to single agent trastuzumab-based neoadjuvant therapy.

Neoadjuvant letrozole plus taselisib versus letrozole plus placebo in postmenopausal women with oestrogen receptor-positive, HER2-negative, early-stage breast cancer (LORELEI): a multicentre, randomised, double-blind, placebo-controlled, phase 2 trial.

BACKGROUND: Endocrine therapy-based neoadjuvant treatment for luminal breast cancer allows efficient testing of new combinations before surgery. The activation of the phosphatidylinositol-3-kinase (PI3K) pathway is a known mechanism of resistance to endocrine therapy. Taselisib is an oral, selective PI3K inhibitor with enhanced activity against PIK3CA-mutant cancer cells. The LORELEI trial tested whether taselisib in combination with letrozole would result in an increased proportion of objective responses and pathological complete responses. METHODS: In this multicentre, randomised, double-blind, parallel-cohort, placebo-controlled phase 2, study, we enrolled postmenopausal women (aged ≥18 years) with histologically confirmed, oestrogen receptor (ER)-positive, HER2-negative, stage I-III, operable breast cancer, from 85 hospitals in 22 countries worldwide. To be eligible, patients had have an Eastern Cooperative Oncology Group (ECOG) performance status 0-1, adequate organ function, and had to have evaluable tumour tissue for PIK3CA genotyping. Patients were randomly assigned (1:1) by means of a permuted block algorithm (block size of four) via an interactive voice or web-based response system, to receive letrozole (2·5 mg/day orally, continuously) with either 4 mg of oral taselisib or placebo (on a 5 days-on, 2 days-off schedule) for 16 weeks, followed by surgery. Randomisation was stratified by tumour size and nodal status. Site staff, patients, and the sponsor were masked to treatment assignment. Coprimary endpoints were the proportion of patients who achieved an objective response by centrally assessed breast MRI and a locally assessed pathological complete response in the breast and axilla (ypT0/Tis, ypN0) at surgery in all randomly assigned patients and in patients with PIK3CA-mutant tumours. Analyses were done in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, number NCT02273973, and is closed to accrual. FINDINGS: Between Nov 12, 2014, and Aug 12, 2016, 334 participants were enrolled and randomly assigned to receive letrozole and placebo (n=168) or letrozole and taselisib (n=166). Median follow-up was 4·9 months (IQR 4·7-5·1). The study met one of its primary endpoints: the addition of taselisib to letrozole was associated with a higher proportion of patients achieving an objective response in all randomly assigned patients (66 [39%] of 168 patients in the placebo group vs 83 [50%] of 166 in the taselisib group; odds ratio [OR] 1·55, 95% CI 1·00-2·38; p=0·049) and in the PIK3CA-mutant subset (30 [38%] of 79 vs 41 [56%] of 73; OR 2·03, 95% CI 1·06-3·88; p=0·033). No significant differences were observed in pathological complete response between the two groups, either in the overall population (three [2%] of 166 in the taselisib group vs one [1%] of 168 in the placebo group; OR 3·07 [95% CI 0·32-29·85], p=0·37) or in the PIK3CA-mutant cohort (one patient [1%) vs none [0%]; OR not estimable, p=0·48). The most common grade 3-4 adverse events in the taselisib group were gastrointestinal (13 [8%] of 167 patients), infections (eight [5%]), and skin-subcutaneous tissue disorders (eight [5%]). In the placebo group, four (2%) of 167 patients had grade 3 or worse vascular disorders, two (1%) had gastrointestinal disorders, and two (1%) patients had grade 3 or worse infections and infestations. There was no grade 4 hyperglycaemia and grade 3 cases were asymptomatic. Serious adverse events were more common in the taselisib group (eight [5%] patients with infections and seven [4%] with gastrointestinal effects) than in the placebo group (one [1%] patient each with grade 3 postoperative wound and haematoma infection, grade 4 hypertensive encephalopathy, grade 3 acute cardiac failure, and grade 3 breast pain). One death occurred in the taselisib group, which was not considered to be treatment-related. INTERPRETATION: The increase in the proportion of patients who achieved an objective response from the addition of taselisib to endocrine therapy in a neoadjuvant setting is consistent with the clinical benefit observed in hormone receptor-positive, HER2-negative, metastatic breast cancer. FUNDING: Genentech and F Hoffmann-La Roche.

Everolimus plus Exemestane for Hormone Receptor-Positive Advanced Breast Cancer: A PAM50 Intrinsic Subtype Analysis of BOLERO-2.

BACKGROUND: The prognostic and predictive value of the two nonluminal (human epidermal growth factor receptor 2 [HER2]-enriched and basal-like) subtypes within advanced hormone receptor-positive (HR+) breast cancer is currently unknown. MATERIALS AND METHODS: This study retrospectively analyzed 261 tumors (80.7% primary; 19.3% metastatic) from the BOLERO-2 study; BOLERO-2 randomized 724 patients with advanced HR+/HER2-negative breast cancer to everolimus plus exemestane or placebo plus exemestane. Tumors were classified using a PAM50 subtype predictor. Multivariable Cox regression analyses tested the independent prognostic significance of PAM50, and associations between PAM50 subtypes and treatment upon progression-free survival (PFS) were evaluated. RESULTS: Subtype distribution was 46.7% luminal A (n = 122), 21.5% HER2-enriched (n = 56), 15.7% luminal B (n = 41), 14.2% normal-like (n = 37), and 1.9% basal-like (n = 5); HER2-enriched subtypes were more common in metastatic versus primary tumors (32.0% vs. 18.7%; p = .038). Median PFS differences between luminal and nonluminal (6.7 vs. 5.2 months; adjusted hazard ratio, 0.66; 95% confidence interval [CI], 0.47-0.94; p = .020) and HER2-enriched and non-HER2-enriched subtypes (5.2 vs. 6.2 months; adjusted hazard ratio, 1.53; 95% CI, 1.07-2.19; p = .019) were significant. Everolimus plus exemestane significantly improved median PFS versus placebo plus exemestane among patients with HER2-enriched tumors (5.8 vs. 4.1 months; adjusted hazard ratio, 0.49; 95% CI, 0.26-0.90; p = .034); however, the association between HER2-enriched tumors and everolimus benefit was nonsignificant (p = .433). CONCLUSION: The HER2-enriched subtype was identified in a substantial proportion of advanced HR+/HER2-negative breast tumors, and was a consistent biomarker of poor prognosis. Tailored therapies are therefore needed for HER2-enriched tumors in the advanced HR+/HER2-negative breast cancer setting. IMPLICATIONS FOR PRACTICE: Using 261 tumor samples from the BOLERO-2 phase III clinical trial, this study shows that a substantial proportion (20%-30%) of hormone receptor-positive (HR+)/human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancers do not have a luminal A or B gene expression profile. This group of patients with nonluminal disease has a poor survival outcome regardless of the addition of everolimus to exemestane. This is the second study that confirms the prognostic value of this biomarker. Overall, these findings indicate a necessity to design novel clinical trials targeting nonluminal disease within HR+/HER2-negative breast cancer.

Analysis of the PD-1/PD-L1 axis in human autoimmune thyroid disease: Insights into pathogenesis and clues to immunotherapy associated thyroid autoimmunity.

Autoimmune thyroid diseases (AITDs), i.e., Graves' disease (GD) and Hashimoto thyroiditis (HT), are the most prevalent organ-specific autoimmune diseases, but their pathogenesis is still incompletely understood. The PD-1/PD-L1 pathway is an important mechanism of peripheral tolerance that has not been investigated in AITDs. Here, we report the analysis of the expression of PD-1, PD-L1 and PD-L2 in PBMCs, infiltrating thyroid lymphocytes (ITLs) and in thyroid follicular cells (TFCs) in GD, HT and multinodular goiter (MNG) patients and healthy controls PBMCs (HC). By combining flow cytometry, tissue immunofluorescence and induction experiments on primary and thyroid cell line cultures, we show that: 1) while PD-1+ T cells are moderately expanded in PBMCs from GD vs HC, approximately half of T cells in the infiltrate are PD-1+ including some PD-1hi; 2) PD-L1, but not PD-L2, is expressed by 81% of GD glands and in 25% of non-autoimmune glands; 3) PD-L1, was expressed by TFCs in areas that also contain abundant PD-1 positive T cells but; 4) co-localization in TFCs indicated only partial overlap between the smaller areas of the PD-L1+ and the larger areas of HLA class II+ expression; 5) IFNγ is capable of inducing PD-L1 in >90% of TFCs in primary cultures and cell lines. Collectively these results indicate that the PD-1/PD-L1 axis is operative in AITD glands and may restrain the autoimmune response. Yet the discrepancy between easy induction in vitro and the limited expression in vivo (compared to HLA) suggests that PD-L1 expression in vivo is partially inhibited in GD and HT glands. In conclusions 1) the PD-1/PD-L1 pathway is activated in AITD glands but probably not to the extent to inhibit disease progression and 2) Thyroid autoimmunity arising after PD-1/PD-L1 blocking therapies in cancer patients may result from interfering PD-1/PD-L1 tolerance mechanism in thyroid with minimal (focal) thyroiditis. Finally acting on the PD-1/PD-L1 pathway could be a new approach to treat AITD and other organ-specific autoimmunity in the future.

HER2-enriched subtype as a predictor of pathological complete response following trastuzumab and lapatinib without chemotherapy in early-stage HER2-positive breast cancer (PAMELA): an open-label, single-group, multicentre, phase 2 trial.

BACKGROUND: HER2-positive breast cancer consists of four intrinsic molecular subtypes-luminal A, luminal B, HER2-enriched, and basal-like-and a normal-like subtype, with the HER2-enriched subtype having the highest activation of the EGFR-HER2 pathway. We aimed to test the hypothesis that patients with the HER2-enriched subtype benefit the most from dual HER2 blockade. METHODS: PAMELA is an open-label, single-group, phase 2 trial done in 19 hospitals in Spain. We recruited female patients aged at least 18 years with previously untreated, centrally confirmed HER2-positive, stage I-IIIA invasive breast cancer regardless of hormone receptor status. Patients were given lapatinib (1000 mg per day orally) and trastuzumab (loading dose of 8 mg/kg, followed by 6 mg/kg every 3 weeks intravenously) for 18 weeks; hormone receptor-positive patients were additionally given letrozole (2·5 mg per day orally; if menopausal) or tamoxifen (20 mg per day orally; if premenopausal). Surgery was done 1-3 weeks after the last dose of study treatment. Intrinsic molecular subtypes of tumour biopsy samples taken at baseline (day 0) and day 14 were determined with the PAM50 predictor. The primary outcome was the ability of the HER2-enriched subtype to predict pathological complete response at the time of surgery. The primary outcome was assessed in the evaluable population (ie, all patients who had initial tumour biopsy samples available and who underwent definitive surgery) and safety was assessed in all patients who received at least one part of study treatment. This study is registered with ClinicalTrials.gov, number NCT01973660, and is completed. FINDINGS: Between Oct 28, 2013, and Nov 26, 2015, we recruited 151 patients, of whom 14 (9%) discontinued treatment and 137 (91%) completed treatment as planned. At baseline, most patients had the HER2-enriched subtype (101 [67%]), followed by luminal A (22 [15%]), luminal B (16 [11%]), basal-like (nine [6%]), and normal-like (three [2%]) subtypes. At the time of surgery, 46 (30%, 95% CI 23-39) of 151 patients had pathological complete response in the breast. 41 (41%, 31-51) of 101 patients with the HER2-enriched subtype and five (10%, 4-23) of 50 patients with non-HER2-enriched subtypes achieved pathological complete response at the time of surgery (odds ratio 6·2, 95% CI 2·3-16·8; p=0·0004). INTERPRETATION: The HER2-enriched subtype can identify patients with HER2-positive breast cancer who are likely to benefit from dual HER2 blockade therapies. FUNDING: GlaxoSmithKline, Susan Komen Foundation, CERCA Programme-Generalitat de Catalunya, Banco Bilbao Vizcaya Argentaria Foundation, Pas a Pas, and the Breast Cancer Research Foundation.

Assessing Tumor-infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method From the International Immunooncology Biomarkers Working Group: Part 1: Assessing the Host Immune Response, TILs in Invasive Breast Carcinoma and Ductal Carcinoma In Situ, Metastatic Tumor Deposits and Areas for Further Research.

Assessment of tumor-infiltrating lymphocytes (TILs) in histopathologic specimens can provide important prognostic information in diverse solid tumor types, and may also be of value in predicting response to treatments. However, implementation as a routine clinical biomarker has not yet been achieved. As successful use of immune checkpoint inhibitors and other forms of immunotherapy become a clinical reality, the need for widely applicable, accessible, and reliable immunooncology biomarkers is clear. In part 1 of this review we briefly discuss the host immune response to tumors and different approaches to TIL assessment. We propose a standardized methodology to assess TILs in solid tumors on hematoxylin and eosin sections, in both primary and metastatic settings, based on the International Immuno-Oncology Biomarker Working Group guidelines for TIL assessment in invasive breast carcinoma. A review of the literature regarding the value of TIL assessment in different solid tumor types follows in part 2. The method we propose is reproducible, affordable, easily applied, and has demonstrated prognostic and predictive significance in invasive breast carcinoma. This standardized methodology may be used as a reference against which other methods are compared, and should be evaluated for clinical validity and utility. Standardization of TIL assessment will help to improve consistency and reproducibility in this field, enrich both the quality and quantity of comparable evidence, and help to thoroughly evaluate the utility of TILs assessment in this era of immunotherapy.

Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immuno-Oncology Biomarkers Working Group: Part 2: TILs in Melanoma, Gastrointestinal Tract Carcinomas, Non-Small Cell Lung Carcinoma and Mesothelioma, Endometrial and Ovarian Carcinomas, Squamous Cell Carcinoma of the Head and Neck, Genitourinary Carcinomas, and Primary Brain Tumors.

Assessment of the immune response to tumors is growing in importance as the prognostic implications of this response are increasingly recognized, and as immunotherapies are evaluated and implemented in different tumor types. However, many different approaches can be used to assess and describe the immune response, which limits efforts at implementation as a routine clinical biomarker. In part 1 of this review, we have proposed a standardized methodology to assess tumor-infiltrating lymphocytes (TILs) in solid tumors, based on the International Immuno-Oncology Biomarkers Working Group guidelines for invasive breast carcinoma. In part 2 of this review, we discuss the available evidence for the prognostic and predictive value of TILs in common solid tumors, including carcinomas of the lung, gastrointestinal tract, genitourinary system, gynecologic system, and head and neck, as well as primary brain tumors, mesothelioma and melanoma. The particularities and different emphases in TIL assessment in different tumor types are discussed. The standardized methodology we propose can be adapted to different tumor types and may be used as a standard against which other approaches can be compared. Standardization of TIL assessment will help clinicians, researchers and pathologists to conclusively evaluate the utility of this simple biomarker in the current era of immunotherapy.

Quantification of HER family receptors in breast cancer.

The clinical success of trastuzumab in breast cancer taught us that appropriate tumor evaluation is mandatory for the correct identification of patients eligible for targeted therapies. Although HER2 protein expression by immunohistochemistry (IHC) and gene amplification by fluorescence in situ hybridization (FISH) assays are routinely used to select patients to receive trastuzumab, both assays only partially predict response to the drug. In the case of epidermal growth factor receptor (EGFR), the link between the presence of the receptor or its amplification and response to anti-EGFR therapies could not be demonstrated. Even less is known for HER3 and HER4, mainly due to lack of robust and validated assays detecting these proteins. It is becoming evident that, besides FISH and IHC, we need better assays to quantify HER receptors and categorize the patients for individualized treatments. Here, we present the current available methodologies to measure HER family receptors and discuss the clinical implications of target quantification.

NUMB controls p53 tumour suppressor activity.

NUMB is a cell fate determinant, which, by asymmetrically partitioning at mitosis, controls cell fate choices by antagonising the activity of the plasma membrane receptor of the NOTCH family. NUMB is also an endocytic protein, and the NOTCH-NUMB counteraction has been linked to this function. There might be, however, additional functions of NUMB, as witnessed by its proposed role as a tumour suppressor in breast cancer. Here we describe a previously unknown function for human NUMB as a regulator of tumour protein p53 (also known as TP53). NUMB enters in a tricomplex with p53 and the E3 ubiquitin ligase HDM2 (also known as MDM2), thereby preventing ubiquitination and degradation of p53. This results in increased p53 protein levels and activity, and in regulation of p53-dependent phenotypes. In breast cancers there is frequent loss of NUMB expression. We show that, in primary breast tumour cells, this event causes decreased p53 levels and increased chemoresistance. In breast cancers, loss of NUMB expression causes increased activity of the receptor NOTCH. Thus, in these cancers, a single event-loss of NUMB expression-determines activation of an oncogene (NOTCH) and attenuation of the p53 tumour suppressor pathway. Biologically, this results in an aggressive tumour phenotype, as witnessed by findings that NUMB-defective breast tumours display poor prognosis. Our results uncover a previously unknown tumour suppressor circuitry.

A whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still lacking?

The search for understanding immunotherapy response has sparked interest in diverse areas of oncology, with artificial intelligence (AI) and radiomics emerging as promising tools, capable of gathering large amounts of information to identify suitable patients for treatment. The application of AI in radiology has grown, driven by the hypothesis that radiology images capture tumor phenotypes and thus could provide valuable insights into immunotherapy response likelihood. However, despite the rapid growth of studies, no algorithms in the field have reached clinical implementation, mainly due to the lack of standardized methods, hampering study comparisons and reproducibility across different datasets. In this review, we performed a comprehensive assessment of published data to identify sources of variability in radiomics study design that hinder the comparison of the different model performance and, therefore, clinical implementation. Subsequently, we conducted a use-case meta-analysis using homogenous studies to assess the overall performance of radiomics in estimating programmed death-ligand 1 (PD-L1) expression. Our findings indicate that, despite numerous attempts to predict immunotherapy response, only a limited number of studies share comparable methodologies and report sufficient data about cohorts and methods to be suitable for meta-analysis. Nevertheless, although only a few studies meet these criteria, their promising results underscore the importance of ongoing standardization and benchmarking efforts. This review highlights the importance of uniformity in study design and reporting. Such standardization is crucial to enable meaningful comparisons and demonstrate the validity of biomarkers across diverse populations, facilitating their implementation into the immunotherapy patient selection process.

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression.

Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunotherapy response. However, quantification of PD-L1 status in pathology slides is challenging. Neither manual quantification nor a computer-based mimicking of manual readouts is perfectly reproducible, and the predictive performance of both approaches regarding immunotherapy response is limited. In this study, we developed a deep learning (DL) method to predict PD-L1 status directly from raw IHC image data, without explicit intermediary steps such as cell detection or pigment quantification. We trained the weakly supervised model on PD-L1-stained slides from the non-small cell lung cancer (NSCLC)-Memorial Sloan Kettering (MSK) cohort (N = 233) and validated it on the pan-cancer-Vall d'Hebron Institute of Oncology (VHIO) cohort (N = 108). We also investigated the performance of the model to predict response to immune checkpoint inhibitors (ICI) in terms of progression-free survival. In the pan-cancer-VHIO cohort, the performance was compared with tumor proportion score (TPS) and combined positive score (CPS). The DL model showed good performance in predicting PD-L1 expression (TPS ≥ 1%) in both NSCLC-MSK and pan-cancer-VHIO cohort (AUC 0.88 ± 0.06 and 0.80 ± 0.03, respectively). The predicted PD-L1 status showed an improved association with response to ICIs [HR: 1.5 (95% confidence interval: 1-2.3), P = 0.049] compared with TPS [HR: 1.4 (0.96-2.2), P = 0.082] and CPS [HR: 1.2 (0.79-1.9), P = 0.386]. Notably, our explainability analysis showed that the model does not just look at the amount of brown pigment in the IHC slides, but also considers morphologic factors such as lymphocyte conglomerates. Overall, end-to-end weakly supervised DL shows potential for improving patient stratification for cancer immunotherapy by analyzing PD-L1 IHC, holistically integrating morphology and PD-L1 staining intensity. SIGNIFICANCE: The weakly supervised DL model to predict PD-L1 status from raw IHC data, integrating tumor staining intensity and morphology, enables enhanced patient stratification in cancer immunotherapy compared with traditional pathologist assessment.

Identification of Precise 3D CT Radiomics for Habitat Computation by Machine Learning in Cancer.

Purpose To identify precise three-dimensional radiomics features in CT images that enable computation of stable and biologically meaningful habitats with machine learning for cancer heterogeneity assessment. Materials and Methods This retrospective study included 2436 liver or lung lesions from 605 CT scans (November 2010-December 2021) in 331 patients with cancer (mean age, 64.5 years ± 10.1 [SD]; 185 male patients). Three-dimensional radiomics were computed from original and perturbed (simulated retest) images with different combinations of feature computation kernel radius and bin size. The lower 95% confidence limit (LCL) of the intraclass correlation coefficient (ICC) was used to measure repeatability and reproducibility. Precise features were identified by combining repeatability and reproducibility results (LCL of ICC ≥ 0.50). Habitats were obtained with Gaussian mixture models in original and perturbed data using precise radiomics features and compared with habitats obtained using all features. The Dice similarity coefficient (DSC) was used to assess habitat stability. Biologic correlates of CT habitats were explored in a case study, with a cohort of 13 patients with CT, multiparametric MRI, and tumor biopsies. Results Three-dimensional radiomics showed poor repeatability (LCL of ICC: median [IQR], 0.442 [0.312-0.516]) and poor reproducibility against kernel radius (LCL of ICC: median [IQR], 0.440 [0.33-0.526]) but excellent reproducibility against bin size (LCL of ICC: median [IQR], 0.929 [0.853-0.988]). Twenty-six radiomics features were precise, differing in lung and liver lesions. Habitats obtained with precise features (DSC: median [IQR], 0.601 [0.494-0.712] and 0.651 [0.52-0.784] for lung and liver lesions, respectively) were more stable than those obtained with all features (DSC: median [IQR], 0.532 [0.424-0.637] and 0.587 [0.465-0.703] for lung and liver lesions, respectively; P < .001). In the case study, CT habitats correlated quantitatively and qualitatively with heterogeneity observed in multiparametric MRI habitats and histology. Conclusion Precise three-dimensional radiomics features were identified on CT images that enabled tumor heterogeneity assessment through stable tumor habitat computation. Keywords: CT, Diffusion-weighted Imaging, Dynamic Contrast-enhanced MRI, MRI, Radiomics, Unsupervised Learning, Oncology, Liver, Lung Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Sagreiya in this issue.