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BackgroundCancer seems to have an independent adverse prognostic effect on COVID-19-related mortality, but uncertainty exists regarding its effect across different patient subgroups. We report a population-based analysis of patients hospitalised with COVID-19 with prior or current solid cancer versus those without cancer.MethodsWe analysed data of adult patients registered until 24 May 2020 in the Belgian nationwide database of Sciensano. The primary objective was in-hospital mortality within 30 days of COVID-19 diagnosis among patients with solid cancer versus patients without cancer. Severe event occurrence, a composite of intensive care unit admission, invasive ventilation and/or death, was a secondary objective. These endpoints were analysed across different patient subgroups. Multivariable logistic regression models were used to analyse the association between cancer and clinical characteristics (baseline analysis) and the effect of cancer on in-hospital mortality and on severe event occurrence, adjusting for clinical characteristics (in-hospital analysis).ResultsA total of 13 594 patients (of whom 1187 with solid cancer (8.7%)) were evaluable for the baseline analysis and 10 486 (892 with solid cancer (8.5%)) for the in-hospital analysis. Patients with cancer were older and presented with less symptoms/signs and lung imaging alterations. The 30-day in-hospital mortality was higher in patients with solid cancer compared with patients without cancer (31.7% vs 20.0%, respectively; adjusted OR (aOR) 1.34; 95% CI 1.13 to 1.58). The aOR was 3.84 (95% CI 1.94 to 7.59) among younger patients (<60 years) and 2.27 (95% CI 1.41 to 3.64) among patients without other comorbidities. Severe event occurrence was similar in both groups (36.7% vs 28.8%; aOR 1.10; 95% CI 0.95 to 1.29).ConclusionsThis population-based analysis demonstrates that solid cancer is an independent adverse prognostic factor for in-hospital mortality among patients with COVID-19. This adverse effect was more pronounced among younger patients and those without other comorbidities. Patients with solid cancer should be prioritised in vaccination campaigns and in tailored containment measurements.

AURORA aims to study the processes of relapse in metastatic breast cancer (MBC) by performing multiomics profiling on paired primary tumors and early-course metastases. Among 381 patients (primary tumor and metastasis pairs: 252 TGS, 152 RNA-Seq, 67 SNP Arrays), we found a driver role for GATA1 and MEN1 somatic mutations. Metastases were enriched in ESR1, PTEN, CDH1, PIK3CA and RB1Research.

Disclosures of potential conflicts of interest may be found at the end of this article.

In this review, we discuss biomarkers of response and resistance to PI3K inhibitors (PI3Ki) in estrogen receptor-positive breast cancer, both in the early and advanced settings. We analyse data regarding PIK3CA mutations, PI3K pathway activation, PTEN expression loss, Akt signalling, insulin levels, 18F FDG-PET/CT imaging, FGFR1/2 amplification, KRAS and TP53 mutations. Most of the discussed data comprise retrospective and exploratory studies, hence many results are not conclusive. Therefore, among all of these biomarkers, only PIK3CA mutations have proved to have a predictive value for treatment with the a-selective PI3Ki alpelisib (SOLAR-1 trial) and the b-sparing PI3Ki taselisib (SANDPIPER trial) in the advanced setting. Since the accuracy of current individual biomarkers is not optimal, a composite biomarker, including DNA, RNA and protein expression data, to more precisely assess the PI3K/AKT/mTOR pathway activation status, may arise as a promising approach. Finally, we describe the rational for new combination therapies involving PI3Ki and anti-HER2 agents, chemotherapy, CDK4/6 inhibitors, mTOR inhibitors or new endocrine treatments and discuss the ongoing trials in this field.

HER2-positive disease is an aggressive subtype of breast cancer that has been revolutionized by anti-HER2 directed therapies. Multiple drugs have been developed and are currently in clinical use, including trastuzumab, lapatinib, pertuzumab, T-DM1, and neratinib, alone or combined in 'dual HER2-blockade' regimens. Areas covered: A comprehensive literature review was performed regarding the current state and the future of combination regimens containing anti-HER2 agents, focusing on their efficacy, toxicity, and cost-effectiveness. Expert commentary: The combination of trastuzumab/pertuzumab is approved in all disease settings, while trastuzumab/neratinib is approved in the adjuvant setting and trastuzumab/lapatinib in metastatic disease. Meanwhile, as breast cancer biology and resistance mechanisms become clearer, combinations with drugs like PI3K/Akt/mTOR inhibitors, CDK4/6 inhibitors, anti-PD(L)1 antibodies, endocrine therapy, and new anti-HER2 agents (panHER and HER2 tyrosine kinase inhibitors, bispecific antibodies, anti-HER3 antibodies, and antibody-drug conjugates) are being extensively tested in clinical trials. More specific strategies for the 'triple-positive' (estrogen receptor-positive/HER2-positive) disease are also being explored. However, there is an urgent need for the development of predictive biomarkers for a better tailoring of anti-HER2 directed therapy. This is the only way to further improve clinical outcomes and quality of life and to decrease costs and toxicities of unnecessary treatments.

HER2 þ early breast cancer is a heterogeneous disease, comprising all the intrinsic breast cancer subtypes. The only biomarker available nowadays for anti-HER2 treatment selection is HER2 status itself, but estrogen receptor (ER) status is emerging as a robust predictive marker within HER2 þ disease. In this Perspective, we discuss the biological and clinical differences between patients with HER2 þ /ER-positive (ER þ ) disease versus those with HER2 þ / ER-negative (ER-neg) tumors, namely, short-term and long-term (>5 years after diagnosis) prognosis, response to neoadjuvant treatment and benefit from adjuvant anti-HER2-targeted therapies. We also address other possible biomarkers to be used for patient selection in future clinical trials, such as gene signatures, PAM50 subtypes, tumor-infiltrating lymphocytes, PIK3CA mutations, and changes in Ki67 score during treatment and discuss their limitations. Finally, we suggest new clinical trial designs that can have an impact on clinical practice, aiming to test treatment deescalation separately for patients with HER2 þ /ER þ and HER2 þ /ER-neg tumors. We also propose an integrated classification of HER2 þ disease, comprising DNA, RNA, protein expression, and microenvironment characteristics, in order to identify those tumors that are truly "HER2-addicted" and may benefit the most from anti-HER2 treatment.

Background There are limited data regarding the impact of body mass index (BMI) on outcomes in advanced breast cancer, especially in patients treated with endocrine therapy (ET) + cyclin-dependent kinase 4/6 inhibitors. Methods A pooled analysis of individual patient-level data from MONARCH 2 and 3 trials was performed. Patients were classified according to baseline BMI into underweight (&lt;18.5 kg/m2), normal (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obese (≥30 kg/m2) and divided into 2 treatment groups: abemaciclib + ET vs placebo + ET. The primary endpoint was progression-free survival (PFS) according to BMI in each treatment group. Secondary endpoints were response rate, adverse events according to BMI, and loss of weight (≥5% from baseline) during treatment. Results This analysis included 1138 patients (757 received abemaciclib + ET and 381 placebo + ET). There was no difference in PFS between BMI categories in either group, although normal-weight patients presented a numerically higher benefit with abemaciclib + ET (Pinteraction = .07). Normal and/or underweight patients presented higher overall response rate in the abemaciclib + ET group compared with overweight and/or obese patients (49.4% vs 41.6%, odds ratio = 0.73, 95% confidence interval = 0.54 to 0.99) as well as higher neutropenia frequency (51.0% vs 40.4%, P = .004). Weight loss was more frequent in the abemaciclib + ET group (odds ratio = 3.23, 95% confidence interval = 2.09 to 5.01). Conclusions Adding abemaciclib to ET prolongs PFS regardless of BMI, showing that overweight or obese patients also benefit from this regimen. Our results elicit the possibility of a better effect of abemaciclib in normal and/or underweight patients compared with overweight and/or obese patients. More studies analyzing body composition parameters in patients under treatment with cyclin-dependent kinase 4/6 inhibitors may further clarify this hypothesis.