Completion Rate and Positive Results Reporting Among Immunotherapy Trials in Breast Cancer, 2004-2023.

Importance: Clinical trials are the path to test and introduce new therapies in the clinic. Trials that are unable to produce results represent inefficiency in the system and may also undermine patient confidence in the new drug development process. Objectives: To survey the immunotherapy clinical trial landscape of breast cancer between January 2004 and April 2023 and examine what fraction of trials with primary completion date up to November 30, 2022, failed to report outcome, assessing the proportion of trials that yielded positive results and describing trial features associated with these 2 outcomes. Design, Setting, and Participants: This cross-sectional study included breast cancer immunotherapy trials identified in ClinicalTrials.gov. Trial details and results were retrieved in December 2023. Google Scholar, PubMed, and LARVOL CLIN websites were also searched for reports. Main Outcomes and Measures: Trial outcome reported as abstract or manuscript. Reported trials were categorized as positive (ie, met its end point) or negative. Association between reporting and trial features were tested using Fisher exact test. Results: A total of 331 immuno-oncology trials were initiated in breast cancer by April 2023; 242 trials were phase II, 47 were phase I, and 42 phase III. By setting, 212 studies (64.0%) were conducted in metastatic, 94 (28.4%) in neoadjuvant, and 25 (7.6%) in adjuvant settings. Among phase II and III trials, 168 (59.2%) were nonrandomized. One hundred twenty trials had primary completion dates up to November 30, 2022, of which 30 (25.0%; enrolling a combined 2428 patients) failed to report their outcomes; 7 phase I trials (31.8%), 21 phase II trials (23.6%), and 2 phase III trials (22.2%) were unreported. Single-center studies were significantly more likely to be unreported than multicenter studies (19 of 54 [35.2%] vs 9 of 60 [15.0%]; P = .02). Of the 90 reported trials, 47 (52.2%) and 43 (47.8%) were positive and negative, respectively. Seventeen of 19 (89.5%) of the reported randomized trials (accruing a total of 4189 patients) were negative. Conclusions and Relevance: In this cross-sectional study of immunotherapy breast cancer trials, the large number of trials yielded modest clinical impact. Single-center trials commonly failed to report their outcomes and many phase II studies have not translated into corresponding successful phase III trials.

Clinical impact of drug-drug interactions on abemaciclib in the real-world experience of AB-ITALY study.

Abemaciclib demonstrated clinical benefit in women affected by HR+/HER2- advanced breast cancer (aBC). Drug-drug interactions (DDIs) can lead to reduced treatment efficacy or increased toxicity. This retro-prospective study aimed to evaluate outcomes, DDIs' impact, and toxicities of abemaciclib combined with endocrine therapy in a real-world setting. Patients from 12 referral Italian hospitals with HR+/HER2- aBC who received abemaciclib were included. Clinical data about comorbidities, concurrent medications, outcomes, and adverse events (AE) were collected. Drug-PIN® (Personalized Interactions Network) is a tool recognizing the role of multiple interactions between active and/or pro-drug forms combined with biochemical and demographic patient data. The software was used to define the Drug-PIN score and Drug-PIN tier (green, yellow, dark yellow, and red) for each patient. Univariate and multivariate analyses were performed to identify predictors of patients' PFS or toxicity. One hundred seventy-three patients were included. 13% of patients had >75years. The overall response rate (ORR) was 63%. The general population's median PFS (mPFS) was 22 months (mo), while mOS were not reached. Patients treated with abemaciclib in combination with AI and fulvestrant had a mPFS of 36 and 19 mo, respectively. The most common toxicities were diarrhea, asthenia, and neutropenia detected in 63%,49%, and 49% of patients. The number of concomitant medications and comorbidities were not associated with survival outcomes (22 vs 17 mo, p = 0.068, p = 0.99). Drug-PIN tier from dark yellow to red and Drug-PIN score >12 were associated with shorter PFS compared to no/low-risk DDIs and score <12 (15 vs 23, p = 0.005, p = 0.0017). Drug interaction was confirmed as an independent biomarker in a multivariate model (p = 0.02). No difference in any grade AE, severe toxicities, and diarrhea were detected among different age subgroups. No association was found between Drug-PIN score or Drug-PIN tier and overall toxicity (p = 0.44), severe AEs (p = 0.11), or drug reduction (p = 0.27). The efficacy and safety of abemaciclib plus ET were confirmed in a real-world setting, even in the elderly population and patients with comorbidities. Evaluation of DDIs with Drug-PIN appears to be an independent predictor of PFS.

Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence.

Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning. Beyond detection, AI applications extend to histological subtyping, grading, lymph node assessment, and molecular feature identification, fostering personalized therapy decisions. With rising cancer rates, it is crucial to implement AI to accelerate breakthroughs in clinical practice, benefiting both patients and healthcare providers. However, it is important to recognize that while AI offers powerful automation and analysis tools, it lacks the nuanced understanding, clinical context, and ethical considerations inherent to human pathologists in patient care. Hence, the successful integration of AI into clinical practice demands collaborative efforts between medical experts and computational pathologists to optimize patient outcomes.

Use of Antibody-Drug Conjugates in the Early Setting of Breast Cancer.

Antibody-drug conjugates (ADCs) are anticancer agents with the capacity to selectively deliver their payloads to cancer cells. Antibody-drug conjugates consist of a monoclonal antibody backbone connected by a linker to cytotoxic payloads. Antibody-drug conjugate effect occurs either by directly targeting cancer cells via membrane antigen or through "bystander effect." Antibody-drug conjugates have demonstrated efficacy against various types of tumors, including breast cancer. Ado-trastuzumab emtansine is presently the only approved ADC for the treatment of breast cancer in the early setting, while several ADCs are now approved for metastatic breast cancer. Due to the transformative impact that several ADCs have reported in the setting of advanced breast cancer, researchers are now testing more of such compounds in the early setting, to portend benefits to patients through highly potent anticancer drugs. Ongoing trials hold the potential to transform treatment protocols for early breast cancer in the near future. These trials are aiming at evaluating different treatment modulation approaches, as informed by breast cancer risk of recurrence, including toward treatment de-escalation. Efforts are provided in ongoing clinical trials to identify the patients who will benefit most, to pursue paradigms of precision medicine with the novel ADCs. This review focuses on the potential role of ADCs in early breast cancer, providing an overview of the latest progress in their development and how they are implemented in ongoing clinical trials.

Effect of age on safety and efficacy of novel cancer drugs investigated in early-phase clinical trials.

BACKGROUND: Elderly patients are underrepresented in clinical trials, particularly in early-phase studies. Our study assessed the safety and efficacy of novel anti-cancer treatments investigated in early-phase clinical trials, comparing outcomes between younger and elderly patients. METHODS: This retrospective study analyzed data from patients enrolled in phase I/II trials at our center between January 2014 and April 2021. We evaluated clinicopathologic characteristics, toxicity, and clinical efficacy, categorizing patients into younger (≤ 65 years) and elderly (> 65 years) groups. RESULTS: 419 patients were included with a median age of 56 years. Among these, 107 (26 %) were older than 65 years. Predominant cancers included breast (48 %), lung (10 %), and melanoma (5 %). Patients were treated in 64 trials, predominantly receiving immunotherapy-based (47 %) or targeted therapy-based (45 %) treatment. Elderly presented with poorer ECOG performance status (P = 0.001) and had fewer prior therapy lines (P = 0.01) than younger patients. Grade ≥ 3 adverse events (AEs) were similar across age groups (31 % younger vs 33 % elderly; P = 0.7), including in combination therapy scenarios. However, elderly patients experienced more AEs with antibody-drug conjugates compared to younger counterparts (56 % vs 14 %, P = 0.036) and were more likely to discontinue treatment due to toxicity (15 % vs 7 %; P = 0.011). No significant age-related differences in response rates and survival outcomes were observed across treatment modalities, except for immunotherapy-based regimens for which elderly patients exhibited higher response rates, disease control rates, and prolonged progression-free survival. CONCLUSIONS: Our findings suggest that elderly exhibit comparable safety and efficacy outcomes to younger patients in early-phase clinical trials for new cancer drugs. This underscores the importance of including elderly patients in phase I/II trials to ensure the generalizability of study results and mitigate age-related disparities in cancer treatment access.

The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy.

Multigene prognostic genomic assays have become indispensable in managing early breast cancer (EBC), offering crucial information for risk stratification and guiding adjuvant treatment strategies in conjunction with traditional clinicopathological parameters. The American Society of Clinical Oncology (ASCO) guidelines endorse these assays, though some clinical contexts still lack definitive recommendations. The dynamic landscape of EBC management demands further refinement and optimization of genomic assays to streamline their incorporation into clinical practice. The breast cancer community is poised at the brink of transformative advances in enhancing the clinical utility of genomic assays, aiming to significantly improve the precision and effectiveness of both diagnosis and treatment for women with EBC. This article methodically examines the testing methodologies, clinical validity and utility, costs, diagnostic frameworks, and methodologies of the established genomic tests, including the Oncotype Dx Breast Recurrence Score®, MammaPrint, Prosigna®, EndoPredict®, and Breast Cancer Index (BCI). Among these tests, Prosigna and EndoPredict® have at present been validated only on a prognostic level, while Oncotype Dx, MammaPrint, and BCI hold both a prognostic and predictive role. Oncologists and pathologists engaged in the management of EBC will find in this review a thorough comparison of available genomic assays, as well as strategies to optimize the utilization of the information derived from them.

Invasive lobular breast cancer: Focus on prevention, genetics, diagnosis, and treatment.

Invasive lobular cancer (ILC) is the most common of the breast cancer special types, accounting for up to 15% of all breast malignancies. The distinctive biological features of ILC include the loss of the cell adhesion molecule E-cadherin, which drives the tumor's peculiar discohesive growth pattern, with cells arranged in single file and dispersed throughout the stroma. Typically, such tumors originate in the lobules, are more commonly bilateral compared to invasive ductal cancer (IDC) and require a more accurate diagnostic examination through imaging. They are luminal in molecular subtype, and exhibit estrogen and progesterone receptor positivity and HER2 negativity, thus presenting a more unpredictable response to neoadjuvant therapies. There has been a significant increase in research focused on this distinctive breast cancer subtype, including studies on its pathology, its clinical and surgical management, and the high-resolution definition of its genomic profile, as well as the development of new therapeutic perspectives. This review will summarize the heterogeneous pattern of this unique disease, focusing on challenges in its comprehensive clinical management and on future insights and research objectives.

Standardized molecular pathology workflow for ctDNA-based ESR1 testing in HR+/HER2- metastatic breast cancer.

Mutations in the estrogen receptor alpha gene (ESR1) can lead to resistance to endocrine therapy (ET) in hormone receptor-positive (HR+)/ HER2- metastatic breast cancer (MBC). ESR1 mutations can be detected in up to 40 % of patients pretreated with ET in circulating tumor DNA (ctDNA). Data from prospective randomized trials highlight those patients with HR+/HER2- MBC with detectable ESR1 mutations experience better outcomes when receiving novel selective estrogen receptor degraders (SERDs). There is a high need for optimizing ESR1 testing strategies on liquid biopsy samples in HR+/HER2- MBC, including a hugh quality workflow implementation and molecular pathology reporting standardization. Our manuscript aims to elucidate the clinical and biological rationale for ESR1 testing in MBC, while critically examining the currently available guidelines and recommendations for this specific type of molecular testing on ctDNA. The objective will extend to the critical aspects of harmonization and standardization, specifically focusing on the pathology laboratory workflow. Finally, we propose a clear and comprehensive model for reporting ESR1 testing results on ctDNA in HR+/HER2- MBC.

The evolving landscape of metastatic HER2-positive, hormone receptor-positive Breast Cancer.

Therapeutic agents targeting Human Epidermal Growth Factor Receptor 2 (HER2) demonstrated to positively impact the prognosis of HER2-positive breast cancer. HER2-positive breast cancer can present either as hormone receptor-negative or positive, defining Triple-positive breast cancer (TPBC). TPBC demonstrate unique gene expression profiles, showing reduced HER2-driven gene expression, as recapitulated by a higher proportion of Luminal-type intrinsic subtypes. The different molecular landscape of TPBC dictates distinctive clinical features, including reduced chemotherapy sensitivity, different patterns of recurrence, and better overall prognosis. Cross-talk between HER2 and hormone receptor signaling seems to be critical to determine resistance to HER2-directed agents. Accordingly, superior outcomes have been achieved with the use of endocrine therapy, representing the first subtype-specific pharmacological intervention unique to this subgroup. Additional targeted agents capable to tackle resistance mechanisms to anti-HER2, hormone agents, or both might further improve the efficacy of treatments, such as PI3K/AKT/mTOR inhibitors, particularly in a biomarker-enriched setting, and CDK4/6-inhibitors, with preliminary data suggesting a role of PAM50 subtyping to predict higher benefits in luminal tumors. Finally, the distinct biology of triple-positive tumors may yield the rationale for considering combinations within antibody-drug conjugate regimens. Accordingly, in this review, we summarized the current evidence and rationale for considering TPBC as a different entity, in which distinct therapeutical approaches leveraging on the different biological profile of TPBC may result in superior anticancer regimens and improved patient-centric outcomes.

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.

PARP Inhibitors for Breast Cancer Treatment: A Review.

Importance: Poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitors have revolutionized the treatment of patients with germline BRCA1/2-associated breast cancer, representing the first targeted therapy capable of improving outcomes in patients with hereditary tumors. However, resistance to PARP inhibitors occurs in almost all patients. Observations: This narrative review summarizes the biological rationale behind the use of PARP inhibitors in breast cancer, as well as the available evidence, recent progress, and potential future applications of these agents. Recent studies have shown that the benefit of PARP inhibitors extends beyond patients with germline BRCA1/2-associated metastatic breast cancer to patients with somatic BRCA1/2 variants and to those with germline PALB2 alterations. Moreover, these agents proved to be effective both in the metastatic and adjuvant settings. However, patients with metastatic breast cancer usually do not achieve the long-term benefit from PARP inhibitors observed in other tumor types. Mechanisms of resistance have been identified, but how to effectively target them is largely unknown. Ongoing research is investigating both novel therapeutics and new combination strategies to overcome resistance. PARP1-selective inhibitors, by sparing the hematological toxic effects induced by the PARP2 blockade, are promising agents to be combined with chemotherapy, antibody-drug conjugates, and other targeted therapies. Conclusions and Relevance: Although the efficacy of PARP inhibitors is well established, many questions persist. Future research should focus on identifying predictive biomarkers and therapeutic strategies to overcome resistance. Integrating well-designed translational efforts into all clinical studies is thereby crucial to laying the groundwork for future insights from ongoing research.

Mutational Analysis of Circulating Tumor DNA in Patients With Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer Receiving Palbociclib: Results From the TREnd Trial.

PURPOSE: To identify prognostic circulating biomarkers to cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i), we performed a mutational analysis on circulating tumor DNA (ctDNA) samples from patients included in the TREnd trial, which randomly assigned patients to receive the CDK4/6i palbociclib alone or with the endocrine treatment (ET) to which they had progressed. METHODS: Forty-six patients were enrolled in this substudy. Plasma was collected before treatment (T0), after the first cycle of therapy (T1), and at the time of progression (T2). ctDNA hybridization and capture were performed using the Illumina TruSight Tumor 170 Kit. Acquired mutations were confirmed by digital polymerase chain reaction. Progression-free survival analysis was estimated using the Kaplan-Meier method and compared with the log-rank test. RESULTS: The most frequently mutated genes at T0 were ESR1 (23%), PIK3CA (17%), AR, FGFR2, and TP53 (10%). Mutations in ESR1 at T0 conferred higher risk of progression in the entire population (P = .02) and in patients treated with palbociclib + ET (P = .04). ESR1 mutation effect remained significant after correction for clinical variables (P = .03). PIK3CA mutations at T0 were not prognostic, but higher risk of progression was observed when a broader analysis of PI3K pathway was performed (P = .04). At T2, we observed the emergence of nine new mutations in seven genes. CONCLUSION: Mutations in ESR1 and in PI3K pathway genes at T0 were associated with worse prognosis in palbociclib-treated patients. We describe the emergence of newly acquired mutations in palbociclib-treated patients, which might potentially affect subsequent treatment.

PD-L1 testing in metastatic triple-negative breast cancer: Interobserver and interplatform reproducibility of CE-IVD assays for CPS and IC scores.

PD-L1 test is recommended in different types of tumors to select patients eligible for immune checkpoint inhibitors (ICI) therapy. Several factors make this test challenging in metastatic triple-negative breast cancer (mTNBC). Different assays and platforms are available, each associated with distinct scoring systems and threshold values specific to the ICI compound used, i.e. CPS≥10 for pembrolizumab and IC ≥ 1 % for atezolizumab. Our objective was to assess the consistency of PD-L1 testing in mTNBC by examining interobserver and interassay reproducibility. We assessed n = 60 mTNBC samples for PD-L1 testing using 22C3 pharmDx assay on a Dako Autostainer Link 48 and VENTANA PD-L1 (SP263) on a Ventana BenchMark Ultra. Additionally, a subset of n = 19 samples was tested using the SP142 assay, also on the Ventana BenchMark Ultra. CPS with both 22C3 and SP263 was independently evaluated by five pathologists, all certified PD-L1 trainers. The IC with SP142 was assessed by three of these pathologists, who have particular expertise in breast pathology. Following the computation of the intraclass correlation coefficient (ICC) for each assay and their respective thresholds, we assessed the agreement between different raters and assays using Fleiss's κ, with a 95 % confidence interval (CI). Overall, we observed a significant (p < 0.001) ICC with both CPS assays [22C3 = 0.939 (CI:0.913-0.96); SP263 = 0.972 (CI:0.96-0.982); combined 22C3-SP263 = 0.909 (CI:0.874-0.938)]. Fleiss's κ confirmed an almost perfect agreement among pathologists and assays: 22C3 = 0.938 (CI:0.857-1.018); SP263 = 0.972 (CI:0.890-1.052); combined 22C3-SP263 = 0.907 (CI:0.869-0.945). Perfect inter-rater agreement was reached considering IC. This study establishes the reliability of assessing CPS in mTNBC using either the 22C3 pharmDx, as employed in the KEYNOTE studies, or the VENTANA SP263 assay. Each assay must be used on its designated platform, namely the Dako for 22C3 pharmDx and the Ventana for VENTANA SP263. It is important to remark that CPS and IC identify different patient cohorts and, therefore, are not interchangeable.

Baseline Tumor Size as Prognostic Index in Patients With Advanced Solid Tumors Receiving Experimental Targeted Agents.

BACKGROUND: Baseline tumor size (BTS) has been associated with outcomes in patients with cancer treated with immunotherapy. However, the prognostic impact of BTS on patients receiving targeted therapies (TTs) remains undetermined. METHODS: We reviewed data of patients with advanced solid tumors consecutively treated within early-phase clinical trials at our institution from 01/2014 to 04/2021. Treatments were categorized as immunotherapy-based or TT-based (biomarker-matched or not). BTS was calculated as the sum of RECIST1.1 baseline target lesions. RESULTS: A total of 444 patients were eligible; the median BTS was 69 mm (IQR 40-100). OS was significantly longer for patients with BTS lower versus higher than the median (16.6 vs. 8.2 months, P < .001), including among those receiving immunotherapy (12 vs. 7.5 months, P = .005). Among patients receiving TT, lower BTS was associated with longer PFS (4.7 vs. 3.1 months, P = .002) and OS (20.5 vs. 9.9 months, P < .001) as compared to high BTS. However, such association was only significant among patients receiving biomarker-matched TT, with longer PFS (6.2 vs. 3.3 months, P < .001) and OS (21.2 vs. 6.7 months, P < .001) in the low-BTS subgroup, despite a similar ORR (28% vs. 22%, P = .57). BTS was not prognostic among patients receiving unmatched TT, with similar PFS (3.7 vs. 4.4 months, P = .30), OS (19.3 vs. 11.8 months, P = .20), and ORR (33% vs. 28%, P = .78) in the 2 BTS groups. Multivariate analysis confirmed that BTS was independently associated with PFS (P = .03) and OS (P < .001) but not with ORR (P = .11). CONCLUSIONS: Higher BTS is associated with worse survival outcomes among patients receiving biomarker-matched, but not biomarker-unmatched TT.

Evaluation of the Geographical Accessibility of Genome-Matched Clinical Trials on a National Experience.

BACKGROUND: Molecular-driven oncology allows oncologists to identify treatments that match a cancer's genomic profile. Clinical trials are promoted as an effective modality to deliver a molecularly matched treatment. We explore the role of geographical accessibility in Italy, and its impact on patient access to clinical trials. MATERIAL AND METHODS: We retrospectively reviewed molecular data from a single-institutional case series of patients receiving next-generation sequencing testing between March 2019 and July 2020. Actionable alterations were defined as the ones with at least one matched treatment on Clinicaltrials.gov at the time of genomic report signature. We then calculated the hypothetical distance to travel to reach the nearest assigned clinical trial. RESULTS: We identified 159 patients eligible for analysis. One hundred and one could be potentially assigned to a clinical trial in Italy, and the median distance that patients needed to travel to reach the closest location with a suitable clinical trial was 76 km (interquartile range = 127.46 km). Geographical distribution of clinical trials in Italy found to be heterogeneous, with Milan and Naples being the areas with a higher concentration. We then found that the probability of having a clinical trial close to a patient's hometown increased over time, according to registered studies between 2015 and 2020. CONCLUSIONS: The median distance to be travelled to the nearest trial was generally acceptable for patients, and trials availability is increasing. Nevertheless, many areas are still lacking trials, so efforts are required to increase and homogenize the possibilities to be enrolled in clinical trials for Italian patients with cancer.

Cardiotoxicity of Agents Used in Patients With Breast Cancer.

Cancer and cardiovascular diseases are the two major causes of mortality, morbidity, and disability worldwide. The improvement in effective therapeutic options for the management of breast cancer (BC) has led to an increased number of BC survivors, who can experience long-term toxicities from cancer treatments. Adverse events including cardiovascular toxicities must be considered in light of effectiveness of recently approved drugs for BC treatment, including elacestrant, tucatinib, neratinib, olaparib, the immune checkpoint inhibitors, trastuzumab deruxtecan, or sacituzumab govitecan. Many cancer drugs affect the cardiovascular system with a range of clinical manifestations. Prompt diagnosis and treatment as well as a multidisciplinary approach involving a cardio-oncologist is optimal for management of these cardiovascular events.

Immune-Related Adverse Event Likelihood Score Identifies "Pure" IRAEs Strongly Associated With Outcome in a Phase I-II Trial Population.

BACKGROUND: Immune-related adverse events (IRAE) pose a significant diagnostic and therapeutic challenge in patients treated with immune-oncology (IO) drugs. IRAEs have been suggested to correlate with better outcome, but studies are conflicting. Estimating the true incidence of IRAEs is particularly difficult in the early phase I/II trial setting. A key issue is the lack of IRAE diagnostic criteria, necessary to discriminate "pure" IRAEs from other treatment-related adverse events not sustained by an autoimmune process. METHODS: In patients treated with immune-oncology (IO) drugs in phases I-II trials at our institute, we identified high confidence (HC) or low confidence (LC) IRAEs by clinical consensus. We empirically developed an IRAE likelihood score (ILS) based on commonly available clinical data. Correlation with outcome was explored by multivariate Cox analysis. To mitigate immortal time-bias, analyses were conducted (1) at 2-month landmark and (2) modeling IRAEs as time-dependent covariate. RESULTS: Among 202 IO-treated patients, 29.2% developed >1 treatment-related adverse events (TRAE). Based on ILS >5, we classified patients in no IRAE (n = 143), HC IRAE (n = 24), or LC IRAE (n = 35). hazard ratios (HR) for HC were significantly lower than LC patients (HR for PFS ranging 0.24-0.44, for OS 0.18-0.23, all P < .01). CONCLUSION: ILS provides a simple system to identify bona fide IRAEs, pruning for other treatment-related events likely due to different pathophysiology. Applying stringent criteria leads to lower and more reliable estimates of IRAE incidence and identifies events with significant impact on survival.

Advancing equitable and personalized cancer care: Novel applications and priorities of artificial intelligence for fairness and inclusivity in the patient care workflow.

Patient care workflows are highly multimodal and intertwined: the intersection of data outputs provided from different disciplines and in different formats remains one of the main challenges of modern oncology. Artificial Intelligence (AI) has the potential to revolutionize the current clinical practice of oncology owing to advancements in digitalization, database expansion, computational technologies, and algorithmic innovations that facilitate discernment of complex relationships in multimodal data. Within oncology, radiation therapy (RT) represents an increasingly complex working procedure, involving many labor-intensive and operator-dependent tasks. In this context, AI has gained momentum as a powerful tool to standardize treatment performance and reduce inter-observer variability in a time-efficient manner. This review explores the hurdles associated with the development, implementation, and maintenance of AI platforms and highlights current measures in place to address them. In examining AI's role in oncology workflows, we underscore that a thorough and critical consideration of these challenges is the only way to ensure equitable and unbiased care delivery, ultimately serving patients' survival and quality of life.

Pan-cancer analysis of antibody-drug conjugate targets and putative predictors of treatment response.

BACKGROUND: Antibody-drug conjugates (ADCs) are a rapidly expanding class of compounds in oncology. Our goal was to assess the expression of ADC targets and potential downstream determining factors of activity across pan-cancer and normal tissues. MATERIALS AND METHODS: ADCs in clinical trials (n = 121) were identified through ClinicalTrials.gov, corresponding to 54 targets. Genes potentially implicated in treatment response were identified in the literature. Gene expression from The Cancer Genome Atlas (9000+ cancers of 31 cancer types), the Genotype-Tissue Expression database (n = 19,000 samples from 31 normal tissue types), and the TNMplot.com (n = 12,494 unmatched primary and metastatic samples) were used in this analysis. To compare relative expression across and within tumour types we used pooled normal tissues as reference. RESULTS: For most ADC targets, mRNA levels correlated with protein expression. Pan-cancer target expression distributions identified appealing cancer types for each ADC development. Co-expression of multiple targets was common and suggested opportunities for ADC combinations. Expression levels of genes potentially implicated in ADC response downstream of the target might provide additional information (e.g. TOP1 was highly expressed in many tumour types, including breast and lung cancers). Metastatic compared to primary tissues overexpressed some ADCs targets. Single sample "targetgram" plots were generated to visualise the expression of potentially competing ADC targets and resistance/sensitivity markers highlighting high inter-patient heterogeneity. Off-cancer target expression only partially explains adverse events, while expression of determinants of payload activity explained more of the observed toxicities. CONCLUSION: Our findings draw attention to new therapeutic opportunities for ADCs that can be tested in the clinic and our web platform (https://tnmplot.com) can assist in prioritising upcoming ADC targets for clinical development.