Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer

Importance

The association of tumor-infiltrating lymphocyte (TIL) abundance in breast cancer tissue with cancer recurrence and death in patients with early-stage triple-negative breast cancer (TNBC) who are not treated with adjuvant or neoadjuvant chemotherapy is unclear.

Objective

To study the association of TIL abundance in breast cancer tissue with survival among patients with early-stage TNBC who were treated with locoregional therapy but no chemotherapy.

Design, Setting, and Participants

Retrospective pooled analysis of individual patient-level data from 13 participating centers in North America (Rochester, Minnesota; Vancouver, British Columbia, Canada), Europe (Paris, Lyon, and Villejuif, France; Amsterdam and Rotterdam, the Netherlands; Milan, Padova, and Genova, Italy; Gothenburg, Sweden), and Asia (Tokyo, Japan; Seoul, Korea), including 1966 participants diagnosed with TNBC between 1979 and 2017 (with follow-up until September 27, 2021) who received treatment with surgery with or without radiotherapy but no adjuvant or neoadjuvant chemotherapy.

Exposure

TIL abundance in breast tissue from resected primary tumors.

Main Outcomes and Measures

The primary outcome was invasive disease-free survival [iDFS]. Secondary outcomes were recurrence-free survival [RFS], survival free of distant recurrence [distant RFS, DRFS], and overall survival. Associations were assessed using a multivariable Cox model stratified by participating center.

Results

This study included 1966 patients with TNBC (median age, 56 years [IQR, 39-71]; 55% had stage I TNBC). The median TIL level was 15% (IQR, 5%-40%). Four-hundred seventeen (21%) had a TIL level of 50% or more (median age, 41 years [IQR, 36-63]), and 1300 (66%) had a TIL level of less than 30% (median age, 59 years [IQR, 41-72]). Five-year DRFS for stage I TNBC was 94% (95% CI, 91%-96%) for patients with a TIL level of 50% or more, compared with 78% (95% CI, 75%-80%) for those with a TIL level of less than 30%; 5-year overall survival was 95% (95% CI, 92%-97%) for patients with a TIL level of 50% or more, compared with 82% (95% CI, 79%-84%) for those with a TIL level of less than 30%. At a median follow-up of 18 years, and after adjusting for age, tumor size, nodal status, histological grade, and receipt of radiotherapy, each 10% higher TIL increment was associated independently with improved iDFS (hazard ratio [HR], 0.92 [0.89-0.94]), RFS (HR, 0.90 [0.87-0.92]), DRFS (HR, 0.87 [0.84-0.90]), and overall survival (0.88 [0.85-0.91]) (likelihood ratio test, P < 10e-6).

Conclusions and Relevance

In patients with early-stage TNBC who did not undergo adjuvant or neoadjuvant chemotherapy, breast cancer tissue with a higher abundance of TIL levels was associated with significantly better survival. These results suggest that breast tissue TIL abundance is a prognostic factor for patients with early-stage TNBC.

Clinical trial inclusion in patients with relapsed/refractory neuroblastoma following the European Precision Cancer Medicine trial MAPPYACTS

INTRODUCTION

Despite poor survival for patients with relapsed or refractory neuroblastoma, only 10-16% of patients are reported to be included in early phase trials. This study aimed to explore the impact of molecular profiling within the prospective precision cancer medicine trial MAPPYACTS (NCT02613962) on subsequent early phase trial recruitment and treatment by matched targeted therapies in this population.

METHODS AND MATERIALS

Clinical data from all French patients with relapsed/refractory neuroblastoma enrolled in MAPPYACTS were analyzed for subsequent matched/non-matched targeted treatment based on clinical tumor board (CMTB) recommendations.

RESULTS

From 93 patients with neuroblastoma included in French centers, 78 (84%) underwent whole exome and RNA sequencing and were discussed in the CMTB. Higher rate of successful sequencing analysis was observed in patients with relapsed disease compared to those with refractory disease (p = 0.0002). Among the 50 patients that presented with a new disease relapse/progression after the CMTB recommendations, 35 patients (70%) had at least one actionable alteration identified on the tumor at the time of relapse. Eighteen patients (36%) were included in an early phase clinical trial, 11 of these with a matched agent, 7 with a non-matched treatment; 13 patients were included in the AcSé ESMART trial. Five patients (10%) received a matched targeted therapy outside a clinical trial.

CONCLUSION

Patients with neuroblastoma in the European MAPPYACTS trial were more likely to be included in early phase trials compared to previous reports. Early deep sequencing at first treatment failure, comprehensive therapeutic discussions in molecular tumor boards and innovative trials like AcSé -ESMART improve access to innovative therapies for patients with relapsed/refractory neuroblastoma.

CLINICAL TRIAL REGISTRATION

NCT02613962.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Moving toward precision medicine to predict drug sensitivity in patients with metastatic breast cancer

Tumor heterogeneity represents a major challenge in breast cancer, being associated with disease progression and treatment resistance. Precision medicine has been extensively applied to dissect tumor heterogeneity and, through a deeper molecular understanding of the disease, to personalize therapeutic strategies. In the last years, technological advances have widely improved the understanding of breast cancer biology and several trials have been developed to translate these new insights into clinical practice, with the ultimate aim of improving patients' outcomes. In the era of molecular oncology, genomics analyses and other methodologies are shaping a new treatment algorithm in breast cancer care. In this manuscript, we review the main steps of precision medicine to predict drug sensitivity in breast cancer from a translational point of view. Genomic developments and their clinical implications are discussed, along with technological advancements that could broaden precision medicine applications. Current achievements are put into perspective to provide an overview of the state-of-art of breast cancer precision oncology as well as to identify future research directions.

Genomic landscape of liquid biopsy mutations in TP53 and DNA damage genes in cancer patients

Next-generation sequencing (NGS) assays based on plasma cell-free DNA (cfDNA) are increasingly used for clinical trials inclusion. Their optimized limit of detection applied to a large number of genes leads to the identification of mutations not confirmed in tissue. It becomes essential to describe the characteristics and consequences of these liquid biopsy-only mutations. In the STING protocol (Gustave Roussy, NCT04932525), 542 patients with advanced solid cancer had cfDNA-based and tissue-based NGS analysis (performed by FoundationOne® Liquid CDx and FoundationOne CDx™, respectively). Mutations identified in the liquid biopsy but not in the paired tissue were considered as liquid biopsy-only mutations irrespective of their variant allelic frequency (VAF). Out of 542 patients, 281 (51.8%) harbored at least one liquid biopsy-only mutation. These patients were significantly older, and more heavily pretreated. Liquid biopsy-only mutations occurring in TP53, and in DDR genes (ATM, CHEK2, ATR, BRCA2, and BRCA1) accounted for 90.8% of all the mutations. The median VAF of these mutations was generally low (0.37% and 0.40% for TP53 and DDR genes respectively). The variant type repartition depended on the gene. Liquid biopsy-only mutations affected hotspot in TP53 codon 273, 125, 195, 176, 237 or 280 and ATM codon 2891 and 3008. In a subset of 37 patients, 75.0%, 53.5% and 83.3% of the liquid biopsy-only mutations occurring respectively in ATM, TP53, and CHEK2 were confirmed in the matching whole blood sample. Although liquid biopsy-only mutations makes the interpretation of liquid biopsy results more complex, they have distinct characteristics making them more easily identifiable.

Patient-Reported Quality of Life 6 Years After Breast Cancer

This cohort study assesses quality-of-life trajectories up to 6 years after breast cancer diagnosis among individuals in France.

Genomic Profiling of Metastatic Castration-Resistant Prostate Cancer Samples Resistant to Androgen Receptor Pathway Inhibitors

PURPOSE

The androgen receptor axis inhibitors (ARPI; e.g., enzalutamide, abiraterone acetate) are administered in daily practice for men with metastatic castration-resistant prostate cancer (mCRPC). However, not all patients respond, and mechanisms of both primary and acquired resistance remain largely unknown.

EXPERIMENTAL DESIGN

In the prospective trial MATCH-R (NCT02517892), 59 patients with mCRPC underwent whole-exome sequencing (WES) and/or RNA sequencing (RNA-seq) of samples collected before starting ARPI. Also, 18 patients with mCRPC underwent biopsy at time of resistance. The objectives were to identify genomic alterations associated with resistance to ARPIs as well as to describe clonal evolution. Associations of genomic and transcriptomic alterations with primary resistance were determined using Wilcoxon and Fisher exact tests.

RESULTS

WES analysis indicated that no single-gene genomic alterations were strongly associated with primary resistance. RNA-seq analysis showed that androgen receptor (AR) gene alterations and expression levels were similar between responders and nonresponders. RNA-based pathway analysis found that patients with primary resistance had a higher Hedgehog pathway score, a lower AR pathway score and a lower NOTCH pathway score than patients with a response. Subclonal evolution and acquisition of new alterations in AR-related genes or neuroendocrine differentiation are associated with acquired resistance. ARPIs do not induce significant changes in the tumor transcriptome of most patients; however, programs associated with cell proliferation are enriched in resistant samples.

CONCLUSIONS

Low AR activity, activation of stemness programs, and Hedgehog pathway were associated with primary ARPIs' resistance, whereas most acquired resistance was associated with subclonal evolution, AR-related events, and neuroendocrine differentiation. See related commentary by Slovin, p. 4323.

Individual Participant Data Network Meta-Analysis of Neoadjuvant Chemotherapy or Chemoradiotherapy in Esophageal or Gastroesophageal Junction Carcinoma

PURPOSE

The optimal neoadjuvant treatment for resectable carcinoma of the thoracic esophagus (TE) or gastroesophageal junction (GEJ) remains a matter of debate. We performed an individual participant data (IPD) network meta-analysis (NMA) of randomized controlled trials (RCTs) to study the effect of chemotherapy or chemoradiotherapy, with a focus on tumor location and histology subgroups.

PATIENTS AND METHODS

All, published or unpublished, RCTs closed to accrual before December 31, 2015 and having compared at least two of the following strategies were eligible: upfront surgery (S), chemotherapy followed by surgery (CS), and chemoradiotherapy followed by surgery (CRS). All analyses were conducted on IPD obtained from investigators. The primary end point was overall survival (OS). The IPD-NMA was analyzed by a one-step mixed-effect Cox model adjusted for age, sex, tumor location, and histology. The NMA was registered in PROSPERO (CRD42018107158).

RESULTS

IPD were obtained for 26 of 35 RCTs (4,985 of 5,807 patients) corresponding to 12 comparisons for CS-S, 12 for CRS-S, and four for CRS-CS. CS and CRS led to increased OS when compared with S with hazard ratio (HR) = 0.86 (0.75 to 0.99), P = .03 and HR = 0.77 (0.68 to 0.87), P < .001 respectively. The NMA comparison of CRS versus CS for OS gave a HR of 0.90 (0.74 to 1.09), P = .27 (consistency P = .26, heterogeneity P = .0038). For CS versus S, a larger effect on OS was observed for GEJ versus TE tumors (P = .036). For the CRS versus S and CRS versus CS, a larger effect on OS was observed for women (P = .003, .012, respectively).

CONCLUSION

Neoadjuvant chemotherapy and chemoradiotherapy were consistently better than S alone across histology, but with some variation in the magnitude of treatment effect by sex for CRS and tumor location for CS. A strong OS difference between CS and CRS was not identified.

Insights adjusting for non-adherence in randomized clinical trials: a reanalysis of an adjuvant trial of tamoxifen duration in early breast cancer

BACKGROUND

Several randomized clinical trials provide evidence of the survival benefit of extended adjuvant tamoxifen in women with estrogen receptor (ER)-positive early breast cancer (BC). However, non-adherence may lead to underestimate treatment effects using intention to treat (ITT) methods. We reanalyzed a randomized trial using contemporary statistical methods adjusting for non-adherence.

METHODS

The TAM01 study was a phase 3 trial including women with early BC, who had completed 2-3 years of adjuvant tamoxifen between 1986 and 1995. Participants were randomly assigned to continue tamoxifen up to 10 years or to discontinue the treatment at randomization. Invasive disease-free survival (iDFS) and overall survival (OS) were estimated using marginal structural models (MSM) and rank preserving structural failure time model (RPSFTM).

RESULTS

Of 3830 patients enrolled, 2485 were randomized to extended tamoxifen, and 1345 to treatment discontinuation. The 10-year non-adherence rate in the extended group was 27.2%. Among women with ER-positive BC (n = 2402), extended tamoxifen was associated with a 45% and 21% relative improvement in iDFS by MSM and RPSFTM, respectively (Hazard Ratio (HR), 0.55; 95% Confidence Interval (CI), 0.48-0.64 and HR, 0.79; 95%CI, 0.67-0.95, respectively), a considerable greater benefit than in the ITT analysis (HR, 0.90; 95%CI, 0.81-0.99). The OS reanalysis revealed a substantial benefit of extended tamoxifen (MSM: HR, 0.70; 95%CI, 0.59-0.83; RPSFTM: HR, 0.85; 95%CI, 0.67-1.04), compared to the ITT analyses (HR, 0.94; 95%CI, 0.84-1.07).

CONCLUSION

This analysis emphasizes both the importance of adherence to hormonotherapy in hormone-receptor positive early BC and the usefulness of more complex statistical analyses.

Resistance to Selective FGFR Inhibitors in FGFR-Driven Urothelial Cancer

Several fibroblast growth factor receptor (FGFR) inhibitors are approved or in clinical development for the treatment of FGFR-driven urothelial cancer, and molecular mechanisms of resistance leading to patient relapses have not been fully explored. We identified 21 patients with FGFR-driven urothelial cancer treated with selective FGFR inhibitors and analyzed postprogression tissue and/or circulating tumor DNA (ctDNA). We detected single mutations in the FGFR tyrosine kinase domain in seven (33%) patients (FGFR3 N540K, V553L/M, V555L/M, E587Q; FGFR2 L551F) and multiple mutations in one (5%) case (FGFR3 N540K, V555L, and L608V). Using Ba/F3 cells, we defined their spectrum of resistance/sensitivity to multiple selective FGFR inhibitors. Eleven (52%) patients harbored alterations in the PI3K-mTOR pathway (n = 4 TSC1/2, n = 4 PIK3CA, n = 1 TSC1 and PIK3CA, n = 1 NF2, n = 1 PTEN). In patient-derived models, erdafitinib was synergistic with pictilisib in the presence of PIK3CA E545K, whereas erdafitinib-gefitinib combination was able to overcome bypass resistance mediated by EGFR activation.

SIGNIFICANCE

In the largest study on the topic thus far, we detected a high frequency of FGFR kinase domain mutations responsible for resistance to FGFR inhibitors in urothelial cancer. Off-target resistance mechanisms involved primarily the PI3K-mTOR pathway. Our findings provide preclinical evidence sustaining combinatorial treatment strategies to overcome bypass resistance. See related commentary by Tripathi et al., p. 1964. This article is featured in Selected Articles from This Issue, p. 1949.

Association of Molecular Profiles and Mutational Status With Distinct Histological Lung Adenocarcinoma Subtypes. An Analysis of the LACE-Bio Data

BACKGROUND

Adjuvant chemotherapy (AC) is indicated for stage II and stage III lung adenocarcinomas (ADC). Using the LACE Bio II database, we analyzed the distribution of various mutations across the subtypes of ADCs and studied the prognostic and predictive roles of PD-L1, TMB, and Tumor Infiltrating Lymphocytes (TILs).

MATERIALS AND METHODS

Clinical and genomic data from the LACE Bio II data were extracted. Patients were divided into ADC subtypes, in which the grouping was done based on their known clinical behavior (Lepidic [LEP], Acinar/Papillary [ACI or PAP], Micropapillary/Solid [MIP or SOL], Mucinous [MUC] and Others). Kaplan-Meier (KM) and log-rank test were used to compare survival based on PD-L1, TMB, TILs and combinations of TMB with PD-L1 and TILs. Adjusted Hazard Ratios (HR) were analyzed with Overall Survival (OS), Disease-Free Survival (DFS) and Lung Cancer-Specific Survival (LCSS) as endpoints.

RESULTS

A total of 375 ADC patients were identified. MIP/SOL was the subtype most commonly positive for various biomarkers. PD-L1 Negative/high TMB was associated with better outcomes in terms of OS (HR = 0.46 [0.23-0.89], P = .021) and DFS (HR = 0.52 [0.30-0.90], P = .02), relative to PD-L1 Negative/low TMB. High TMB predicted worse outcome with AC use in terms of OS (ratio of hazard ratio rHR = 2.75 [1.07-7.04], P = .035). Marked TILs had better outcome with AC for DFS (rHR = 0.22 [0.06-0.87], P = .031 and LCSS (rHR = 0.08 [0.01-0.66], P = .019) respectively. There was also a beneficial effect of AC among patients with Marked TILs/low TMB in terms of DFS (rHR = 0.06 [0.01-0.53], P = .011).

CONCLUSION

High TMB has a prognostic role in resectable lung ADC. The high TMB group had a poor outcome with AC, suggesting that this group may be better served with immune checkpoint therapy.

Does vibration frequency and location influence the effect of neck muscle vibration on postural sway? A cross-sectional study in asymptomatic participants

INTRODUCTION

Postural control is of utmost importance for human functioning. Cervical proprioception is crucial for balance control. Therefore, any change to it can lead to balance problems. Previous studies used neck vibration to change cervical proprioception and showed changes in postural control, but it remains unknown which vibration frequency or location causes the most significant effect. Therefore, this study aimed to investigate the effect of different vibration frequencies and locations on postural sway and to serve as future research protocol guidance.

METHODS

Seventeen healthy young participants were included in the study. We compared postural sway without vibration to postural sway with six different combinations of vibration frequency (80, 100, and 150 Hz) and location (dorsal neck muscles and sternocleidomastoid). Postural sway was evaluated using a force platform. The mean center of pressure (CoP) displacement, the root mean square (RMS), and the mean velocity in the anteroposterior and mediolateral direction were calculated, as well as the sway area. The aligned rank transform tool and a three-way repeated measures ANOVA were used to identify significant differences in postural sway variables.

RESULTS

Neck vibration caused a significant increase in all postural sway variables (p < 0.001). Neither the vibration frequency (p > 0.34) nor location (p > 0.29) nor the interaction of both (p > 0.30) influenced the magnitude of the change in postural sway measured during vibration.

CONCLUSION

Neck muscle vibration significantly changes CoP displacement, mean velocity, RMS, and area. However, we investigated and found that there were no significant differences between the different combinations of vibration frequency and location.

A Case-Only Genome-Wide Interaction Study of Smoking and Bladder Cancer Risk: Results from the COBLAnCE Cohort

Bladder cancer (BC) is the 6th most common cancer worldwide, with tobacco smoking considered as its main risk factor. Accumulating evidence has found associations between genetic variants and the risk of BC. Candidate gene-environment interaction studies have suggested interactions between cigarette smoking and NAT2/GSTM1 gene variants. Our objective was to perform a genome-wide association case-only study using the French national prospective COBLAnCE cohort (COhort to study BLAdder CancEr), focusing on smoking behavior. The COBLAnCE cohort comprises 1800 BC patients enrolled between 2012 and 2018. Peripheral blood samples collected at enrolment were genotyped using the Illumina Global Screening Array with a Multi-Disease drop-in panel. Genotyping data (9,719,614 single nucleotide polymorphisms (SNP)) of 1674, 1283, and 1342 patients were analyzed for smoking status, average tobacco consumption, and age at smoking initiation, respectively. A genome-wide association study (GWAS) was conducted adjusting for gender, age, and genetic principal components. The results suggest new candidate loci (4q22.1, 12p13.1, 16p13.3) interacting with smoking behavior for the risk of BC. Our results need to be validated in other case-control or cohort studies.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges

BACKGROUND

In high-dimensional data (HDD) settings, the number of variables associated with each observation is very large. Prominent examples of HDD in biomedical research include omics data with a large number of variables such as many measurements across the genome, proteome, or metabolome, as well as electronic health records data that have large numbers of variables recorded for each patient. The statistical analysis of such data requires knowledge and experience, sometimes of complex methods adapted to the respective research questions.

METHODS

Advances in statistical methodology and machine learning methods offer new opportunities for innovative analyses of HDD, but at the same time require a deeper understanding of some fundamental statistical concepts. Topic group TG9 "High-dimensional data" of the STRATOS (STRengthening Analytical Thinking for Observational Studies) initiative provides guidance for the analysis of observational studies, addressing particular statistical challenges and opportunities for the analysis of studies involving HDD. In this overview, we discuss key aspects of HDD analysis to provide a gentle introduction for non-statisticians and for classically trained statisticians with little experience specific to HDD.

RESULTS

The paper is organized with respect to subtopics that are most relevant for the analysis of HDD, in particular initial data analysis, exploratory data analysis, multiple testing, and prediction. For each subtopic, main analytical goals in HDD settings are outlined. For each of these goals, basic explanations for some commonly used analysis methods are provided. Situations are identified where traditional statistical methods cannot, or should not, be used in the HDD setting, or where adequate analytic tools are still lacking. Many key references are provided.

CONCLUSIONS

This review aims to provide a solid statistical foundation for researchers, including statisticians and non-statisticians, who are new to research with HDD or simply want to better evaluate and understand the results of HDD analyses.

Abstract 3418: Alterations in PIK3CA/PTEN as resistance mechanisms in lung cancer patients progressing on first-line next generation EGFR/ALK tyrosine kinase inhibitors

Introduction: Advent of targeted therapies has deeply changed treatment of advanced oncogene-addicted non-small cell lung cancer (NSCLC), but development of resistance remains a main issue. Given the efficacy of next generation tyrosine kinase inhibitors (TKIs) against on-target mutations, their first-line administration could increase the relevance of off-target resistance mechanisms. Activating PIK3CA mutations and PTEN loss have been described as putative off-target resistance mechanisms across generations of EGFR TKIs. The role of these alterations in the development of resistance to ALK TKIs has been less described.

MATCH-R trial (NCT02517892) is an ongoing prospective study whose objective is to understand mechanisms of acquired resistance to cancer therapies and develop strategies to overcome it.

Materials and methods: We collected clinical and molecular data of patients (pts) with NSCLC enrolled in the molecular target group (MTG) of MATCH-R trial. We identified pts with EGFR mutations or ALK rearrangements who developed PIK3CA/PTEN alterations in tissue biopsy and/or circulating tumor DNA upon progression to first-line osimertinib/alectinib. We established patient-derived cell lines (PDCL) from the identified MATCH-R pts and we engineered commercial cell lines (CCL) harboring EGFR mutation (PC9) or ALK fusion (H3122) to constitutively express PIK3CA mutations and/or to have a permanent loss of PTEN. Cell viability assays and Western blot studies with different EGFR/ALK/PI3K/mTOR inhibitors were performed.

Results: Of the 186 pts with advanced NSCLC included in the MTG of MATCH-R, 110 (59.1%) harbored EGFR mutations (EGFR+) and 27 (14.5%) ALK rearrangements (ALK+). Among them, 19 received first-line osimertinib and seven first-line alectinib. Five and two pts developed PIK3CA/PTEN alterations in the EGFR+ and ALK+ groups, respectively. In the EGFR+ group, PIK3CA E545K (n=2), R108H, N345K and R357Q mutations were detected. PTEN mutations (F437fs*5 and Y27C) were concomitant with E545K and R357Q mutations, respectively. In both ALK+ pts, a PIK3CA E545K mutation was identified, together with PTEN exon 5 splicing in one case. We confirmed on CCL that PIK3CA E545K mutation, alone or in combination with PTEN loss, confers resistance to second-/third-generation EGFR/ALK TKIs. PTEN loss alone had a moderate

impact on TKIs sensitivity. Overcoming strategies combining EGFR/ALK TKIs with PIK3CA/mTOR inhibitors are being evaluated and will be disclosed at the meeting.

Conclusions: Activating PI3KCA mutations and molecular events leading to PTEN loss are frequent events at resistance to first-line EGFR/ALK TKIs, and can be detected concomitantly. Functional assays confirmed that these alterations act as resistance mechanisms. These observations are of interest as PI3KCA/mTOR inhibitors may have a role in overcoming resistance.

Citation Format: Giorgia Guaitoli, Francesco Facchinetti, Juan David Flórez-Arango, Floriane Braye, Hayato Mizuta, Santiago Ponce-Aix, Damien Vasseur, Ken André Olaussen, Stefan Michiels, Mihaela Aldea, Jordi Remon, Fabrice Barlesi, Benjamin Besse, David Planchard, Luc Friboulet. Alterations in PIK3CA/PTEN as resistance mechanisms in lung cancer patients progressing on first-line next generation EGFR/ALK tyrosine kinase inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3418.

Favoring the hierarchical constraint in penalized survival models for randomized trials in precision medicine

BACKGROUND

The research of biomarker-treatment interactions is commonly investigated in randomized clinical trials (RCT) for improving medicine precision. The hierarchical interaction constraint states that an interaction should only be in a model if its main effects are also in the model. However, this constraint is not guaranteed in the standard penalized statistical approaches. We aimed to find a compromise for high-dimensional data between the need for sparse model selection and the need for the hierarchical constraint.

RESULTS

To favor the property of the hierarchical interaction constraint, we proposed to create groups composed of the biomarker main effect and its interaction with treatment and to perform the bi-level selection on these groups. We proposed two weighting approaches (Single Wald (SW) and likelihood ratio test (LRT)) for the adaptive lasso method. The selection performance of these two approaches is compared to alternative lasso extensions (adaptive lasso with ridge-based weights, composite Minimax Concave Penalty, group exponential lasso and Sparse Group Lasso) through a simulation study. A RCT (NSABP B-31) randomizing 1574 patients (431 events) with early breast cancer aiming to evaluate the effect of adjuvant trastuzumab on distant-recurrence free survival with expression data from 462 genes measured in the tumour will serve for illustration. The simulation study illustrates that the adaptive lasso LRT and SW, and the group exponential lasso favored the hierarchical interaction constraint. Overall, in the alternative scenarios, they had the best balance of false discovery and false negative rates for the main effects of the selected interactions. For NSABP B-31, 12 gene-treatment interactions were identified more than 20% by the different methods. Among them, the adaptive lasso (SW) approach offered the best trade-off between a high number of selected gene-treatment interactions and a high proportion of selection of both the gene-treatment interaction and its main effect.

CONCLUSIONS

Adaptive lasso with Single Wald and likelihood ratio test weighting and the group exponential lasso approaches outperformed their competitors in favoring the hierarchical constraint of the biomarker-treatment interaction. However, the performance of the methods tends to decrease in the presence of prognostic biomarkers.

Integrative pan-cancer genomic and transcriptomic analyses of refractory metastatic cancer

Metastatic relapse after treatment is the leading cause of cancer mortality, and known resistance mechanisms are missing for most treatments administered to patients. To bridge this gap, we analyze a pan-cancer cohort (META-PRISM) of 1,031 refractory metastatic tumors profiled via whole-exome and transcriptome sequencing. META-PRISM tumors, particularly prostate, bladder, and pancreatic types, displayed the most transformed genomes compared to primary untreated tumors. Standard-of-care resistance biomarkers were identified only in lung and colon cancers - 9.6% of META-PRISM tumors, indicating that too few resistance mechanisms have received clinical validation. In contrast, we verified the enrichment of multiple investigational and hypothetical resistance mechanisms in treated compared to non-treated patients, thereby confirming their putative role in treatment resistance. Additionally, we demonstrated that molecular markers improve six-month survival prediction, particularly in patients with advanced breast cancer. Our analysis establishes the utility of META-PRISM cohort for investigating resistance mechanisms and performing predictive analyses in cancer.

Abstract PD9-05: Stromal tumor-infiltrating lymphocytes identify early-stage triple-negative breast cancer patients with favorable outcomes at 10-year follow-up in the absence of systemic therapy: a pooled analysis of 1835 patients

Background: The prognostic value of stromal tumor-infiltrating lymphocytes (TILs) as a biomarker for triple-negative breast cancer (TNBC) has been extensively demonstrated in patients (pts) receiving (neo)adjuvant systemic therapy. In addition, several small studies suggest that a subset of pts with early-stage TNBC and high TILs have excellent long-term outcomes, even in the absence of systemic therapy [1-3]. However, data on the absolute risk of TNBC recurrence according to TIL levels in the absence of systemic therapy are limited and critical to inform the design of future systemic therapy de-escalation clinical trials.

Methods: We conducted an individual patient data pooled analysis of 12 international cohorts of pts with TNBC treated with locoregional therapy but no systemic therapy. TNBC was defined as tumors with estrogen and progesterone receptor of &lt; 1% and HER2 negative (IHC 0, 1+ or IHC 2+ and FISH negative) per local evaluation. TILs were locally assessed in hematoxylin & eosin-stained slides according to the International Immuno-Oncology Biomarker Working Group guidelines (www.tilsinbreastcancer.org). We used the Kaplan-Meier method to assess survival outcomes according to prespecified TIL thresholds: 30% and 50%. Confidence intervals (CI) for survival probabilities were calculated using a percentile bootstrap method. The primary endpoint was invasive disease-free survival (iDFS, STEEP 2.0 definition). Key secondary outcomes included recurrence-free survival (RFS), distant disease-free survival (DDFS) and overall survival (OS).

Results: 1,835 pts diagnosed with TNBC between 1982 and 2017 who did not receive systemic therapy were included. The median age at diagnosis was 56 (IQR 38-71). Menopausal status was known in 1,184 women, of whom 78% were post-menopausal. The median tumor size was 2.0 cm (IQR 1.2-2.6). Most pts (87%) had no axillary lymph node involvement (N0). Most tumors were invasive ductal carcinoma (74%) and grade 3 (70%). The median level of TILs was 15% (IQR 5-40). The median duration of follow-up was 30.4 years (95% CI 29.9, 31.1). A total of 950 (52%) iDFS, 828 (45%) RFS, 767 (42%) DDFS events, and 604 (33%) deaths were observed. In multivariable analyses, higher TILs were independently associated with improved iDFS, RFS, DDFS, and OS beyond clinicopathological factors (likelihood ratio p&lt; 10e-6). Each 10% increment in stromal TILs was associated with an 8% (95% CI: 6-11), 10% (95% CI: 7-13), and 13% (95% CI: 10-15) reduction in the risk of experiencing an iDFS, RFS or DDFS event, and with a 12% (95% CI: 9-15) reduction in the risk of death. iDFS, RFS, DDFS and OS rates according to different TIL thresholds and nodal status are shown in the Table. Of note, the RFS estimates (which exclude second non-breast primaries and contralateral breast cancers) were consistently higher than the iDFS counterparts (which include both), consistent with a high rate of contralateral breast cancers and second primary tumors in this cohort. Notably, patients with node-negative—and especially stage I—TNBC with high TILs had excellent survival rates at 10-year follow-up.

Conclusion: TILs are highly prognostic in pts with systemically untreated early-stage TNBC. Pts with pN0 (and especially stage I) TNBC with high TILs exhibited very favorable long-term outcomes even in the absence of systemic therapy. These data define the natural history of TIL-rich TNBC pts and are crucial to identifying the optimal patient population for future chemotherapy and immunotherapy de-escalation clinical trials.

References:

[1] Leon-Ferre et al, 2017, PMID: 28913760

[2] Park et al, 2019, PMID: 31566659

[3] de Jong et al, 2022, PMID: 35353548

Table 5 and 10-year survival endpoints according TIL level, nodal status, and stage

Citation Format: Roberto A. Leon-Ferre, Sarah Flora Jonas, Roberto Salgado, Sherene Loi, Vincent De Jong, Jodi M. Carter, Torsten Nielson, Samuel Leung, Nazia Riaz, Giuseppe Curigliano, Carmen Criscitiello, Vincent Cockenpot, Matteo Lambertini, Vera Suman, Barbro Linderholm, John WM Martens, Carolien HM van Deurzen, Mieke Timmermans, Tatsunori Shimoi, Shu Yazaki, Masayuki Yoshida, Sung-Bae Kim, Hee Jin Lee, Maria Vittoria Dieci, Guillaume Bataillon, Anne Salomon, Fabrice Andre, Marleen Kok, Sabine Linn, Matthew P. Goetz, Stefan Michiels. Stromal tumor-infiltrating lymphocytes identify early-stage triple-negative breast cancer patients with favorable outcomes at 10-year follow-up in the absence of systemic therapy: a pooled analysis of 1835 patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD9-05.

CustOmics: A versatile deep-learning based strategy for multi-omics integration

The availability of patient cohorts with several types of omics data opens new perspectives for exploring the disease's underlying biological processes and developing predictive models. It also comes with new challenges in computational biology in terms of integrating high-dimensional and heterogeneous data in a fashion that captures the interrelationships between multiple genes and their functions. Deep learning methods offer promising perspectives for integrating multi-omics data. In this paper, we review the existing integration strategies based on autoencoders and propose a new customizable one whose principle relies on a two-phase approach. In the first phase, we adapt the training to each data source independently before learning cross-modality interactions in the second phase. By taking into account each source's singularity, we show that this approach succeeds at taking advantage of all the sources more efficiently than other strategies. Moreover, by adapting our architecture to the computation of Shapley additive explanations, our model can provide interpretable results in a multi-source setting. Using multiple omics sources from different TCGA cohorts, we demonstrate the performance of the proposed method for cancer on test cases for several tasks, such as the classification of tumor types and breast cancer subtypes, as well as survival outcome prediction. We show through our experiments the great performances of our architecture on seven different datasets with various sizes and provide some interpretations of the results obtained. Our code is available on (https://github.com/HakimBenkirane/CustOmics).

Abstract PR009: Integrative pan-cancer genomic and transcriptomic analyses of refractory metastatic cancer

Metastatic relapse after treatment is the primary cause of cancer morbidity and mortality. While genetic mechanisms of primary tumors and, to a lesser extent, metastatic cancers have been studied in large cohorts, refractory metastatic tumors are not yet sufficiently characterized. Markers of aggressiveness and resistance that molecular profiling can extract from these tumors have yet to be identified and incorporated into clinical care. In this study, we present a pan-cancer cohort of 1,031 metastatic tumors (which we refer to as META-PRISM) that are resistant to at least one systemic therapy or with no approved treatment options. We retrieved the complete clinical history of patients and performed whole-exome (n=571) and transcriptome sequencing (n=947) for this cohort. The prevalence of detected cancer biomarkers was assessed and compared to an external cohort of primary tumors. In the META-PRISM cohort, we observed an increase in (i) whole-genome duplication frequency, (ii) tumor mutational burden, (iii) germline cancer-predisposing variants, and (iv) somatic alterations in cancer genes, including KRAS, EGFR, CCND1, MYC, and TP53, as compared to the tumor type-matched primary tumors. The most extensive increase in genomic variation at metastatic stage was observed in prostate cancer. We also identified enrichment of standard-of-care resistance biomarkers in most cancer types. However, only 7.6% of tumors harbored at least one such biomarker, indicating that the current understanding of resistance mechanisms remains insufficient. Our cohort demonstrated a significantly improved 6-month survival prediction from models incorporating molecular markers over models with only clinical markers for breast cancer patients and to a lesser extent for other studied tumor types. Overall, our data establish a unique resource for investigating treatment resistance mechanisms and performing predictive analyses in cancer.

Citation Format: Yoann Pradat, Julien Viot, Konstantin Gunbin, Andrei Iurchenko, Marc Deloger, Luigi Cerbone, Guillaume Grisay, Loic Verlingue, Veronique Scott, Stefan Michiels, Antoine Hollebecque, Gerome Jules-Clement, Antoine Laine, Luc Friboulet, Laura Mezquita, Yohann Loriot, Benjamin Besse, Fabrice Andre, Paul-Henry Cournede, Daniel Gautheret, Sergey Nikolaev. Integrative pan-cancer genomic and transcriptomic analyses of refractory metastatic cancer [abstract]. In: Proceedings of the AACR Special Conference: Cancer Metastasis; 2022 Nov 14-17; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_2):Abstract nr PR009.

Molecular analysis for refractory rare cancers: Sequencing battle continues - learnings for the MOSCATO-01 study

BACKGROUND

For patients with metastatic rare cancers, treatments are limited. How systematic tumor sequencing can improve therapeutic possibilities in this population?

PATIENTS AND METHODS

Patients with rare cancer were identified in the MOSCATO-01 trial. Patients' outcome was measured by progression-free survival (PFS) and overall survival (OS).

RESULTS

The most frequently identified histologic subypes were ovarian adenocarcinoma (N = 13), carcinoma of unknown primary (N = 11), and leiomyosarcoma (N = 10). Ninety-nine (39%) of them had at least one targetable cancer molecular alteration Forty-nine patients (50%) received the therapy proposed by the molecular tumor board, and 13 patients (26%, 95%CI 15-41%) achieved a PFS2/PFS1 > 1.3. The median PFS2 on matched treatment subgroup was 2.3 months (95% CI 1.8-3.6) and the median OS was 11.4 months (95% CI 9-15.5).

CONCLUSIONS

The molecular screening of patients with refractory, metastatic rare cancers might increase the therapeutic options. Facilitating access strategy to molecular-driven clinical trials or agnostic-approved treatment is crucial.

Predictive Role of CD36 Expression in HER2-Positive Breast Cancer Patients Receiving Neoadjuvant Trastuzumab

BACKGROUND

Despite huge efforts to identify biomarkers associated with long-term clinical outcomes in patients with early-stage HER2-positive breast cancer (HER2+ BC) treated with (neo)adjuvant anti-HER2 therapy, no reliable predictors have been identified so far. Fatty acid uptake, a process mediated by the transmembrane transporter CD36, has recently emerged as a potential determinant of resistance to anti-HER2 treatments in preclinical HER2+ BC models.

METHODS

Here, we investigated the association between baseline intratumor CD36 gene expression and event-free survival in 180 patients enrolled in the phase III trial Neoadjuvant Lapatinib and/or Trastuzumab Treatment Optimization (NeoALTTO), which randomly assigned stage II-III HER2+ BC patients to receive neoadjuvant lapatinib, trastuzumab, or lapatinib-trastuzumab in combination with chemotherapy. To this aim, we selected NeoALTTO trial patients for whom pretreatment whole transcriptomic data were available. The main study results were validated in an independent cohort of patients enrolled in the neoadjuvant phase II trial NeoSphere.

RESULTS

In 180 NeoALTTO patients, high intratumor CD36 expression was independently associated with worse event-free survival in patients treated with trastuzumab-based therapy (hazard ratio [HR] = 1.72, 95% confidence interval [CI] = 1.20 to 2.46), but not with lapatinib-based (HR = 1.02, 95% CI = 0.68 to 1.53) or trastuzumab-lapatinib-based (HR = 1.08, 95% CI = 0.60 to 1.94) therapy. Among 331 NeoSphere patients evaluated, high CD36 expression was independently associated with worse patient disease-free survival in both the whole study cohort (HR = 1.197, 95% CI = 1.002 to 1.428) and patients receiving trastuzumab-based neoadjuvant therapy (HR = 1.282, 95% CI = 1.049 to 1.568).

CONCLUSIONS

High CD36 expression predicts worse clinical outcomes in early-stage HER2+ BC treated with trastuzumab-based neoadjuvant therapy.

Association of Adherence to Endocrine Therapy Among Patients With Breast Cancer and Potential Drug-Drug Interactions

IMPORTANCE

Suboptimal adherence to endocrine therapy (ET) among patients with hormone-receptor-positive breast cancer significantly affects survival outcomes and is associated with higher hospitalization rates and health care costs. Weak adherence to long-term treatments has multiple determinants, including disease characteristics, treatment adverse effects, and patients' attributes, such as age and comorbidities.

OBJECTIVE

To examine whether potential drug-drug interactions (PDDI) with tamoxifen or aromatase inhibitor were associated with adherence to ET in patients with early and advanced breast cancer.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used anonymized health record data of women with breast cancer who received ET in a private observational primary care database. Patients eligible for analysis included women aged 18 years or older who had a reported diagnosis of breast cancer and received ET with tamoxifen or aromatase inhibitor between 1994 and 2021. Data were analyzed 2021.

EXPOSURES

Adherence to ET during a given year was defined by a medication possession ratio of 80% or greater over 1-year prescription periods. PDDI were categorized into absent, minor (a combination to take into account), moderate (combination requiring precautions for use), major (combination not recommended), and contraindicated according to guidelines in the Claude Bernard Drug Database.

MAIN OUTCOMES AND MEASURES

We used regression models to estimate odds ratios (ORs) and 95% CIs for the associations between adherence and age, baseline comorbidities, PDDI, and adherence to ET during the previous year.

RESULTS

A total of 10 863 patients who were prescribed ET for breast cancer were eligible for the analysis (age 70 years or older, 3509 patients [32.3%]). In the tamoxifen cohort (3564 patients), PDDI were reported in 497 of 3670 patients (13.5%) at baseline (moderate, 254 patients [51.1%]; major, 227 patients [45.7%]), 2047 of 4831 patients (42.4%) at year 1, 1127 of 2751 patients (41.0%) at year 2, 761 of 1861 patients (40.9%) at year 3, 376 of 1058 patients (35.5%) at year 4, and 201 of 593 patients (33.9%) at year 5. In the aromatase inhibitor cohort (7299 patients), PDDI were reported in 592 of 7437 patients (8.0%) at baseline (moderate in 588 of 592 patients [99.3%]), which reached 2875 of 9031 patients (31.8%) at year 1 and ranged between 31.4% (1802 of 5730 patients in year 2) and 32.8% (791 of 2411 in year 4) throughout the study period. No association between adherence and PDDI was found in the tamoxifen (OR, 0.99; 95% CI, 0.91-1.08) or aromatase inhibitor (OR, 1.05; 95% CI, 0.95-1.15) cohort.

CONCLUSIONS AND RELEVANCE

In this cohort of patients with hormone-receptor-positive breast cancer, PDDI with tamoxifen and aromatase inhibitors were not associated with adherence to ET.

High p16 expression and heterozygous RB1 loss are biomarkers for CDK4/6 inhibitor resistance in ER+ breast cancer

CDK4/6 inhibitors combined with endocrine therapy have demonstrated higher antitumor activity than endocrine therapy alone for the treatment of advanced estrogen receptor-positive breast cancer. Some of these tumors are de novo resistant to CDK4/6 inhibitors and others develop acquired resistance. Here, we show that p16 overexpression is associated with reduced antitumor activity of CDK4/6 inhibitors in patient-derived xenografts (n = 37) and estrogen receptor-positive breast cancer cell lines, as well as reduced response of early and advanced breast cancer patients to CDK4/6 inhibitors (n = 89). We also identified heterozygous RB1 loss as biomarker of acquired resistance and poor clinical outcome. Combination of the CDK4/6 inhibitor ribociclib with the PI3K inhibitor alpelisib showed antitumor activity in estrogen receptor-positive non-basal-like breast cancer patient-derived xenografts, independently of PIK3CA, ESR1 or RB1 mutation, also in drug de-escalation experiments or omitting endocrine therapy. Our results offer insights into predicting primary/acquired resistance to CDK4/6 inhibitors and post-progression therapeutic strategies.

External Quality Assessment 2.0: The Importance of a Standardized Implementation of TILs for Daily and Trial Practices

New assays are developed regularly to improve health care for patients. It is important to ensure that assays are performed correctly. Therefore, it is advised to participate in training and proficiency (competence assessment) programs. Tumor infiltrating lymphocytes (TILs) might improve the estimates of response to therapy and prognosis. Herewith, we propose a new training and proficiency program in which each pathologist can train and test themselves regarding TILs (and PDL1) scoring.

Evaluating methods for Lasso selective inference in biomedical research: a comparative simulation study

Background

Variable selection for regression models plays a key role in the analysis of biomedical data. However, inference after selection is not covered by classical statistical frequentist theory, which assumes a fixed set of covariates in the model. This leads to over-optimistic selection and replicability issues.

Methods

We compared proposals for selective inference targeting the submodel parameters of the Lasso and its extension, the adaptive Lasso: sample splitting, selective inference conditional on the Lasso selection (SI), and universally valid post-selection inference (PoSI). We studied the properties of the proposed selective confidence intervals available via R software packages using a neutral simulation study inspired by real data commonly seen in biomedical studies. Furthermore, we present an exemplary application of these methods to a publicly available dataset to discuss their practical usability.

Results

Frequentist properties of selective confidence intervals by the SI method were generally acceptable, but the claimed selective coverage levels were not attained in all scenarios, in particular with the adaptive Lasso. The actual coverage of the extremely conservative PoSI method exceeded the nominal levels, and this method also required the greatest computational effort. Sample splitting achieved acceptable actual selective coverage levels, but the method is inefficient and leads to less accurate point estimates.

The choice of inference method had a large impact on the resulting interval estimates, thereby necessitating that the user is acutely aware of the goal of inference in order to interpret and communicate the results.

Conclusions

Despite violating nominal coverage levels in some scenarios, selective inference conditional on the Lasso selection is our recommended approach for most cases. If simplicity is strongly favoured over efficiency, then sample splitting is an alternative. If only few predictors undergo variable selection (i.e. up to 5) or the avoidance of false positive claims of significance is a concern, then the conservative approach of PoSI may be useful. For the adaptive Lasso, SI should be avoided and only PoSI and sample splitting are recommended. In summary, we find selective inference useful to assess the uncertainties in the importance of individual selected predictors for future applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01681-y.

Complex Disease Individual Molecular Characterization Using Infinite Sparse Graphical Independent Component Analysis

Identifying individual mechanisms involved in complex diseases, such as cancer, is essential for precision medicine. Their characterization is particularly challenging due to the unknown relationships of high-dimensional omics data and their inter-patient heterogeneity. We propose to model individual gene expression as a combination of unobserved molecular mechanisms (molecular components) that may differ between the individuals. Considering a baseline molecular profile common to all individuals, these molecular components may represent molecular pathways differing from the population background. We defined an infinite sparse graphical independent component analysis (isgICA) to identify these molecular components. This model relies on double sparseness: the source matrix sparseness defines the subset of genes involved in each molecular component, whereas the weight matrix sparseness identifies the subset of molecular components associated with each patient. As the number of molecular components is unknown but likely high, we simultaneously inferred it and the weight matrix sparseness using the beta-Bernoulli process (BBP). We simulated data from a double sparse ICA with 10/30 components with specific sparseness structures for 100/500 individuals and 500/1000/5000 genes with different noise variance levels to evaluate the reconstruction of the latent structures by our model. For all simulations, the isgICA was able to reconstruct with higher accuracy than 2 state-of-the-art methods (ica and fastICA) the number of components, the weight and source matrix sparsenesses (correlation simulated/estimated >.8). Applying our model to the expression of 1063 genes of 614 breast cancer patients, the isgICA identified 22 components. According to the source matrix, 7 of these 22 components seemed to be specifically related to 3 known molecular pathways with a prognostic effect in early breast cancer (immune system, proliferation, and stroma invasion). This proposed algorithm provides an insight into individual molecular heterogeneity to better understand complex disease mechanisms.

Informing the development of multidisciplinary interventions to help breast cancer patients return to work: a qualitative study

PURPOSE

Return to work (RTW) after breast cancer (BC) can be a major challenge for patients. Multidisciplinary interventions seem to be effective but the role of digital solutions is under-developed and therefore not evaluated. We explored the preferences, needs, and barriers regarding RTW interventions, including opinions about the use of digital approaches to deliver such interventions.

METHODS

We conducted a qualitative study based on interviews with 30 patients with BC and 18 healthcare providers in four French regions. Emergent themes were identified using thematic content analysis.

RESULTS

Most providers declared that they did not proactively address RTW with patients, mainly due to having other priorities and a lack of knowledge. The following themes emerged: several development and deployment barriers regarding RTW interventions exist, multidisciplinary interventions are preferred, and there is a need to maintain contact between the patient and workplace during sick leave, including pathways and interlocutors that can facilitate RTW. Participants had mostly positive representations of using digital tools to facilitate RTW; however, fear of loss of human contact and the exacerbation of inequalities were identified as possible risks associated with the development of digital-only interventions.

CONCLUSIONS

Interventions blending the needs and preferences of patients with BC and the healthcare system are warranted. A personalized multimodal approach with mixed digital and in-person features has surfaced as a possible solution to address the weaknesses of existing interventions.

IMPLICATIONS FOR CANCER SURVIVORS

Since most women work at the time of diagnosis, it is of particular relevance to build interventions promoting RTW.

Comprehensive genome profiling in patients with metastatic non-small cell lung cancer: the precision medicine phase 2 randomized SAFIR02-Lung trial

PURPOSE

Targeted therapies (TT) and immune checkpoint blockers (ICB) have revolutionized the approach to non-small cell lung cancer (NSCLC) treatment in the era of precision medicine. Their impact as switch maintenance therapy based on molecular characterization is unknown.

EXPERIMENTAL DESIGN

SAFIR02-Lung was an open-label, randomized, phase 2 trial, involving 33 centers in France. We investigated eight TT (substudy-1) and one ICB (substudy-2), compared to standard-of-care as a maintenance strategy in advanced EGFR, ALK wild-type (wt) NSCLC patients without progression after first line chemotherapy, based on high-throughput genome analysis. The primary outcome was progression-free survival (PFS).

RESULTS

Among the 175 patients randomized in substudy-1, 116 received TT (selumetinib, vistusertib, capivasertib, AZD4547, AZD8931, vandetanib, olaparib, savolitinib) and 59 standard-of-care. Median PFS was 2.7 months (95% CI 1.6-2.9) with TT vs. 2.7 months (1.6-4.1) with standard-of-care (HR 0.97, 0.7-1.36; p=0.87). There were no significant differences in PFS within any molecular subgroup. In substudy-2, 183 patients were randomized, 121 received durvalumab and 62 standard-of-care. Median PFS was 3.0 months (2.3-4.4) with durvalumab versus 3.0 months (2.0-5.1) with standard-of-care (HR=0.86; 0.62-1.20; p=0.38). Preplanned subgroup analysis showed an enhanced benefit with durvalumab in patients with PD-L1 Tumor Proportion Score (TPS) ≥ 1%, (n=29, HR=0.29; 0.11-0.75) as compared to PD-L1 <1% (n=31, HR=0.71, 0.31-1.60, interaction p= 0.036).

CONCLUSIONS

Molecular profiling can feasibly be implemented to guide treatment choice for the maintenance strategy in EGFR/ALK wt NSCLC; in the current study it did not lead to substantial treatment benefits beyond durvalumab for PD-L1 ≥ 1 patients.

Association between physical activity and neoadjuvant chemotherapy completion and pathologic complete response in primary breast cancer: the CANTO study

BACKGROUND

Regular physical activity is associated with improved symptom control in patients with breast cancer but its association with chemotherapy completion or response is unclear.

METHODS

Using a prospective design, 1075 breast cancer patients receiving neoadjuvant chemotherapy between March 2012 and February 2017 were studied. Physical activity was assessed using the Global Physical Activity Questionnaire [GPAQ-16], quantified in standardised MET-h/wk. Chemotherapy completion was defined as the proportion of patients completing planned treatment course, requiring dose reduction, or requiring dose delay. Response was evaluated by pathologic complete response (pCR). Associations between physical activity and primary outcomes were assessed using multivariable logistic regression models.

RESULTS

There was no differences between any chemotherapy completion outcome on the basis of physical activity classification. The percent of patients not completing planned treatment was 5.7% for ≦0.33 MET-h/wk, compared with 6.8% for 0.34-16.65 MET-h/wk, and 4.6% for ≥16.6 MET-h/wk (p = 0.52). No significant relationships were observed between physical activity dose classification and pCR for the overall cohort or upon stratification by clinical subtype.

CONCLUSION

Future studies are required to further investigate the relationship between pre-treatment levels of physical activity and function on treatment completion and response in breast and other cancer populations.

CLINICAL TRIAL REGISTRATION

NCT01993498.

Near-Infrared Fluorescence Axillary Reverse Mapping (ARM) Procedure in Invasive Breast Cancer: Relationship between Fluorescence Signal in ARM Lymph Nodes and Clinical Outcomes

Simple Summary

Near-infrared fluorescence axillary reverse mapping (ARM) is a promising procedure for identification and preservation of arm lymphatic drainage during axillary lymph node dissection (ALND). We included 109 patients to analyze the indocyanine green fluorescence signal in ARM lymph nodes after resection. The fluorescence signal from ARM lymph nodes were compared with clinical findings to determine the importance of this criterion on the potential management of patients with ALND. ARM lymph nodes were identified in 94.5% of cases. The mean normalized fluorescence signal intensity value was 0.47 with no significant signal difference between metastatic and non-metastatic ARM lymph nodes. Only the preoperative diagnosis of metastasis in the axillary nodes of patients was significantly associated with a higher ARM node fluorescence signal intensity. Although preliminary results did not show that fluorescence signal intensity is a reliable diagnostic tool, the NIR fluorescence ARM procedure may be useful for ARM lymph node identification.

Abstract

The near-infrared (NIR) fluorescence axillary reverse mapping (ARM) procedure is a promising tool to identify and preserve arm lymphatic drainage during axillary lymph node dissection (ALND). The ARMONIC clinical trial was conducted to validate the technique on a large cohort of patients and to analyze the predictive clinical factors for ARM lymph node metastasis. For the first time, the fluorescence signal intensity from the ARM lymph nodes was measured and correlated with clinical findings. A total of 109 patients with invasive breast cancer and indications of mastectomy and ALND underwent the NIR fluorescence ARM procedure. Indocyanine green was administered by intradermal injection followed by intraoperative identification and resection of the ARM lymph nodes with NIR fluorescence camera guidance. The fluorescence signal intensity and signal distribution were then measured ex vivo and compared with clinical outcomes. ARM lymph nodes were successfully identified by fluorescence in 94.5% of cases. The mean normalized fluorescence signal intensity value was 0.47 with no significant signal difference between metastatic and non-metastatic ARM lymph nodes (p = 0.3728). At the microscopic level, the fluorescence signal distribution was focally intense in lymphoid tissue areas. Only the preoperative diagnosis of metastasis in the axillary nodes of patients was significantly associated with a higher ARM node fluorescence signal intensity (p = 0.0253), though it was not significantly associated with the pathological nodal (pN) status (p = 0.8081). Based on an optimal cut-off fluorescence value, the final sensitivity and specificity of the NIR fluorescence ARM procedure for ARM lymph node metastatic involvement were 64.7% and 47.3%, respectively. Although our preliminary results did not show that fluorescence signal intensity is a reliable diagnostic tool, the NIR fluorescence ARM procedure may be useful for ARM lymph node identification. Clinical trial registration: NCT02994225.

Low level of Fibrillarin, a ribosome biogenesis factor, is a new independent marker of poor outcome in breast cancer

Background

A current critical need remains in the identification of prognostic and predictive markers in early breast cancer. It appears that a distinctive trait of cancer cells is their addiction to hyperactivation of ribosome biogenesis. Thus, ribosome biogenesis might be an innovative source of biomarkers that remains to be evaluated.

Methods

Here, fibrillarin (FBL) was used as a surrogate marker of ribosome biogenesis due to its essential role in the early steps of ribosome biogenesis and its association with poor prognosis in breast cancer when overexpressed. Using 3,275 non-metastatic primary breast tumors, we analysed FBL mRNA expression levels and protein nucleolar organisation. Usage of TCGA dataset allowed transcriptomic comparison between the different FBL expression levels-related breast tumours.

Results

We unexpectedly discovered that in addition to breast tumours expressing high level of FBL, about 10% of the breast tumors express low level of FBL. A correlation between low FBL mRNA level and lack of FBL detection at protein level using immunohistochemistry was observed. Interestingly, multivariate analyses revealed that these low FBL tumors displayed poor outcome compared to current clinical gold standards. Transcriptomic data revealed that FBL expression is proportionally associated with distinct amount of ribosomes, low FBL level being associated with low amount of ribosomes. Moreover, the molecular programs supported by low and high FBL expressing tumors were distinct.

Conclusion

Altogether, we identified FBL as a powerful ribosome biogenesis-related independent marker of breast cancer outcome. Surprisingly we unveil a dual association of the ribosome biogenesis FBL factor with prognosis. These data suggest that hyper- but also hypo-activation of ribosome biogenesis are molecular traits of distinct tumors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09552-x.

The European MAPPYACTS Trial: Precision Medicine Program in Pediatric and Adolescent Patients with Recurrent Malignancies

ABSTRACT

MAPPYACTS (NCT02613962) is an international prospective precision medicine trial aiming to define tumor molecular profiles in pediatric patients with recurrent/refractory malignancies in order to suggest the most adapted salvage treatment. From February 2016 to July 2020, 787 patients were included in France, Italy, Ireland, and Spain. At least one genetic alteration leading to a targeted treatment suggestion was identified in 436 patients (69%) with successful sequencing; 10% of these alterations were considered "ready for routine use." Of 356 patients with follow-up beyond 12 months, 107 (30%) received one or more matched targeted therapies-56% of them within early clinical trials-mainly in the AcSé-ESMART platform trial (NCT02813135). Overall, matched treatment resulted in a 17% objective response rate, and of those patients with ready for routine use alterations, it was 38%. In patients with extracerebral tumors, 76% of actionable alterations detected in tumor tissue were also identified in circulating cell-free DNA (cfDNA).

SIGNIFICANCE

MAPPYACTS underlines the feasibility of molecular profiling at cancer recurrence in children on a multicenter, international level and demonstrates benefit for patients with selected key drivers. The use of cfDNA deserves validation in prospective studies. Our study highlights the need for innovative therapeutic proof-of-concept trials that address the underlying cancer complexity. This article is highlighted in the In This Issue feature, p. 1171.

Dynamics of Long-Term Patient-Reported Quality of Life and Health Behaviors After Adjuvant Breast Cancer Chemotherapy

We aimed to characterize long-term quality of life (QOL) trajectories among patients with breast cancer treated with adjuvant chemotherapy and to identify related patterns of health behaviors.