Generalization optimizing machine learning to improve CT scan radiomics and assess immune checkpoint inhibitors’ response in non-small cell lung cancer: a multicenter cohort study

BackgroundRecent developments in artificial intelligence suggest that radiomics may represent a promising non-invasive biomarker to predict response to immune checkpoint inhibitors (ICIs). Nevertheless, validation of radiomics algorithms in independent cohorts remains a challenge due to variations in image acquisition and reconstruction. Using radiomics, we investigated the importance of scan normalization as part of a broader machine learning framework to enable model external generalizability to predict ICI response in non-small cell lung cancer (NSCLC) patients across different centers.MethodsRadiomics features were extracted and compared from 642 advanced NSCLC patients on pre-ICI scans using established open-source PyRadiomics and a proprietary DeepRadiomics deep learning technology. The population was separated into two groups: a discovery cohort of 512 NSCLC patients from three academic centers and a validation cohort that included 130 NSCLC patients from a fourth center. We harmonized images to account for variations in reconstruction kernel, slice thicknesses, and device manufacturers. Multivariable models, evaluated using cross-validation, were used to estimate the predictive value of clinical variables, PD-L1 expression, and PyRadiomics or DeepRadiomics for progression-free survival at 6 months (PFS-6).ResultsThe best prognostic factor for PFS-6, excluding radiomics features, was obtained with the combination of Clinical + PD-L1 expression (AUC = 0.66 in the discovery and 0.62 in the validation cohort). Without image harmonization, combining Clinical + PyRadiomics or DeepRadiomics delivered an AUC = 0.69 and 0.69, respectively, in the discovery cohort, but dropped to 0.57 and 0.52, in the validation cohort. This lack of generalizability was consistent with observations in principal component analysis clustered by CT scan parameters. Subsequently, image harmonization eliminated these clusters. The combination of Clinical + DeepRadiomics reached an AUC = 0.67 and 0.63 in the discovery and validation cohort, respectively. Conversely, the combination of Clinical + PyRadiomics failed generalizability validations, with AUC = 0.66 and 0.59.ConclusionWe demonstrated that a risk prediction model combining Clinical + DeepRadiomics was generalizable following CT scan harmonization and machine learning generalization methods. These results had similar performances to routine oncology practice using Clinical + PD-L1. This study supports the strong potential of radiomics as a future non-invasive strategy to predict ICI response in advanced NSCLC

Coinfections in Patients With Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Study

Background: The frequency of coinfections and their association with outcomes have not been adequately studied among patients with cancer and coronavirus disease 2019 (COVID-19), a high-risk group for coinfection. Methods: We included adult (≥18 years) patients with active or prior hematologic or invasive solid malignancies and laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection, using data from the COVID-19 and Cancer Consortium (CCC19, NCT04354701). We captured coinfections within ±2 weeks from diagnosis of COVID-19, identified factors cross-sectionally associated with risk of coinfection, and quantified the association of coinfections with 30-day mortality. Results: Among 8765 patients (hospitalized or not; median age, 65 years; 47.4% male), 16.6% developed coinfections: 12.1% bacterial, 2.1% viral, 0.9% fungal. An additional 6.4% only had clinical diagnosis of a coinfection. The adjusted risk of any coinfection was positively associated with age \u3e50 years, male sex, cardiovascular, pulmonary, and renal comorbidities, diabetes, hematologic malignancy, multiple malignancies, Eastern Cooperative Oncology Group Performance Status, progressing cancer, recent cytotoxic chemotherapy, and baseline corticosteroids; the adjusted risk of superinfection was positively associated with tocilizumab administration. Among hospitalized patients, high neutrophil count and C-reactive protein were positively associated with bacterial coinfection risk, and high or low neutrophil count with fungal coinfection risk. Adjusted mortality rates were significantly higher among patients with bacterial (odds ratio [OR], 1.61; 95% CI, 1.33-1.95) and fungal (OR, 2.20; 95% CI, 1.28-3.76) coinfections. Conclusions: Viral and fungal coinfections are infrequent among patients with cancer and COVID-19, with the latter associated with very high mortality rates. Clinical and laboratory parameters can be used to guide early empiric antimicrobial therapy, which may improve clinical outcomes

Gemcitabine-Containing Chemotherapy for the Treatment of Metastatic Myxofibrosarcoma Refractory to Doxorubicin: A Case Series

Background: Myxofibrosarcoma is a type of soft-tissue sarcoma that is associated with high rates of local recurrence and distant metastases. The first-line treatment for metastatic soft-tissue sarcoma has conventionally been doxorubicin-based. Recent evidence suggests that myxofibrosarcoma may be molecularly similar to undifferentiated pleomorphic sarcoma (UPS), which is particularly sensitive to gemcitabine-based therapy. The goal of this study was to evaluate the activity of gemcitabine-containing regimens for the treatment of metastatic myxofibrosarcoma refractory to doxorubicin. Material and Methods: We retrospectively evaluated seven consecutive cases of metastatic myxofibrosarcoma at our institution treated with gemcitabine-based therapy in the second-line setting, after progression on doxorubicin. Baseline clinical and baseline characteristics were collected. Primary endpoints were objective response rate (ORR), progression-free survival (PFS) and overall survival (OS). Results: After progression on first-line doxorubicin, a partial, or complete radiological response was observed in four of seven patients who received gemcitabine-based chemotherapy. With a median follow-up of 14 months, median progression-free and overall survival were 8.5 months and 11.4 months, respectively. Conclusions: Gemcitabine-based chemotherapy was associated with encouraging response rates in this cohort, similar to those seen in UPS. Both entities could be studied together for novel gemcitabine-based regimens

Two Cases of Durable and Deep Responses to Immune Checkpoint Inhibition-Refractory Metastatic Melanoma after Addition of Camu Camu Prebiotic

Camu camu (CC) is a prebiotic that selectively stimulates growth and activity of beneficial gut microbiota. Work in murine models demonstrated that castalagin, the active compound in CC, preferentially binds to beneficial gut microbiome bacteria, promoting a stronger CD8+T cell anti-cancer response. We present two patients with metastatic melanoma whose cancer progressed on immune checkpoint inhibitors (ICIs) and developed clinically significant immune-related adverse events (irAEs). They were rechallenged with ICIs in combination with CC. The first patient is a 71-year-old woman with metastatic melanoma, whose ICI treatment was complicated by immune-related pneumonitis and colitis. Upon progression on maintenance nivolumab, CC was added to nivolumab, leading to a near complete response (CR). The second patient is a 90-year-old man with recurrent unresectable melanoma, treated with nivolumab, complicated by immune-related rash and diabetes. He developed new subcutaneous calf lesions and a metastatic popliteal lymph node. CC was added to nivolumab. One month later, the patient experienced a CR. Both patients have been on nivolumab and CC with durable responses for more than a year, with minimal irAEs. These two cases suggest that CC may modulate the microbiome, synergizing with ICIs to produce deep, durable responses with minimal irAEs

Clinical impact of COVID-19 on patients with cancer treated with immune checkpoint inhibition

BACKGROUND: Patients with cancer who are infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are more likely to develop severe illness and die compared with those without cancer. The impact of immune checkpoint inhibition (ICI) on

Geriatric risk factors for serious COVID-19 outcomes among older adults with cancer: A cohort study from the COVID-19 and Cancer Consortium

Background: Older age is associated with poorer outcomes of SARS-CoV-2 infection, although the heterogeneity of ageing results in some older adults being at greater risk than others. The objective of this study was to quantify the association of a novel geriatric risk index, comprising age, modified Charlson comorbidity index, and Eastern Cooperative Oncology Group performance status, with COVID-19 severity and 30-day mortality among older adults with cancer. Methods: In this cohort study, we enrolled patients aged 60 years and older with a current or previous cancer diagnosis (excluding those with non-invasive cancers and premalignant or non-malignant conditions) and a current or previous laboratory-confirmed COVID-19 diagnosis who reported to the COVID-19 and Cancer Consortium (CCC19) multinational, multicentre, registry between March 17, 2020, and June 6, 2021. Patients were also excluded for unknown age, missing data resulting in unknown geriatric risk measure, inadequate data quality, or incomplete follow-up resulting in unknown COVID-19 severity. The exposure of interest was the CCC19 geriatric risk index. The primary outcome was COVID-19 severity and the secondary outcome was 30-day all-cause mortality; both were assessed in the full dataset. Adjusted odds ratios (ORs) and 95% CIs were estimated from ordinal and binary logistic regression models. Findings: 5671 patients with cancer and COVID-19 were included in the analysis. Median follow-up time was 56 days (IQR 22-120), and median age was 72 years (IQR 66-79). The CCC19 geriatric risk index identified 2365 (41·7%) patients as standard risk, 2217 (39·1%) patients as intermediate risk, and 1089 (19·2%) as high risk. 36 (0·6%) patients were excluded due to non-calculable geriatric risk index. Compared with standard-risk patients, high-risk patients had significantly higher COVID-19 severity (adjusted OR 7·24; 95% CI 6·20-8·45). 920 (16·2%) of 5671 patients died within 30 days of a COVID-19 diagnosis, including 161 (6·8%) of 2365 standard-risk patients, 409 (18·5%) of 2217 intermediate-risk patients, and 350 (32·1%) of 1089 high-risk patients. High-risk patients had higher adjusted odds of 30-day mortality (adjusted OR 10·7; 95% CI 8·54-13·5) than standard-risk patients. Interpretation: The CCC19 geriatric risk index was strongly associated with COVID-19 severity and 30-day mortality. Our CCC19 geriatric risk index, based on readily available clinical factors, might provide clinicians with an easy-to-use risk stratification method to identify older adults most at risk for severe COVID-19 as well as mortality. Funding: US National Institutes of Health National Cancer Institute Cancer Center

Prospective Clinical Genomic Profiling of Ewing Sarcoma: ERF and FGFR1 Mutations as Recurrent Secondary Alterations of Potential Biologic and Therapeutic Relevance.

PurposeEwing sarcoma (ES) is a primitive sarcoma defined by EWSR1-ETS fusions as the primary driver alteration. To better define the landscape of cooperating secondary genetic alterations in ES, we analyzed clinical genomic profiling data of 113 patients with ES, a cohort including more adult patients (> 18 years) and more patients with advanced stage at presentation than previous genomic cohorts.MethodsThe data set consisted of patients with ES prospectively tested with the US Food and Drug Administration-cleared Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets large panel, hybrid capture-based next-generation sequencing assay. To assess the functional significance of ERF loss, we generated ES cell lines with increased expression of ERF and lines with knockdown of ERF. We assessed cell viability, clonogenic growth, and motility in these ES lines and performed transcriptomic and epigenetic analyses. Finally, we validated our findings in vivo using cell line xenografts.ResultsNovel subsets were defined by recurrent secondary alterations in ERF, which encodes an ETS domain transcriptional repressor, in 7% of patients (five truncating mutations, one deep deletion, and two missense mutations) and in FGFR1 in another 2.7% (one amplification and two known activating mutations). ERF alterations were nonoverlapping with STAG2 alterations. In vitro, increased expression of ERF decreased tumor cell growth, colony formation, and motility in two ES cell lines, whereas ERF loss induced cellular proliferation and clonogenic growth. Transcriptomic analysis of cell lines with ERF loss revealed an increased expression of genes and pathways associated with aggressive tumor biology, and epigenetic, chromatin-based studies revealed that ERF competes with EWSR1-FLI1 at ETS-binding sites.ConclusionOur findings open avenues to new insights into ES pathobiology and to novel therapeutic approaches in a subset of patients with ES

Intestinal Akkermansia muciniphila predicts clinical response to PD-1 blockade in patients with advanced non-small-cell lung cancer

43siAside from PD-L1 expression, biomarkers of response to immune checkpoint inhibitors (ICIs) in non-small-cell lung cancer (NSCLC) are needed. In a previous retrospective analysis, we documented that fecal Akkermansia muciniphila (Akk) was associated with clinical benefit of ICI in patients with NSCLC or kidney cancer. In the current study, we performed shotgun-metagenomics-based microbiome profiling in a large cohort of patients with advanced NSCLC (n = 338) treated with first- or second-line ICIs to prospectively validate the predictive value of fecal Akk. Baseline stool Akk was associated with increased objective response rates and overall survival in multivariate analyses, independent of PD-L1 expression, antibiotics, and performance status. Intestinal Akk was accompanied by a richer commensalism, including Eubacterium hallii and Bifidobacterium adolescentis, and a more inflamed tumor microenvironment in a subset of patients. However, antibiotic use (20% of cases) coincided with a relative dominance of Akk above 4.8% accompanied with the genus Clostridium, both associated with resistance to ICI. Our study shows significant differences in relative abundance of Akk that may represent potential biomarkers to refine patient stratification in future studies.reservedopenDerosa, Lisa; Routy, Bertrand; Thomas, Andrew Maltez; Iebba, Valerio; Zalcman, Gerard; Friard, Sylvie; Mazieres, Julien; Audigier-Valette, Clarisse; Moro-Sibilot, Denis; Goldwasser, François; Silva, Carolina Alves Costa; Terrisse, Safae; Bonvalet, Melodie; Scherpereel, Arnaud; Pegliasco, Hervé; Richard, Corentin; Ghiringhelli, François; Elkrief, Arielle; Desilets, Antoine; Blanc-Durand, Felix; Cumbo, Fabio; Blanco, Aitor; Boidot, Romain; Chevrier, Sandy; Daillère, Romain; Kroemer, Guido; Alla, Laurie; Pons, Nicolas; Le Chatelier, Emmanuelle; Galleron, Nathalie; Roume, Hugo; Dubuisson, Agathe; Bouchard, Nicole; Messaoudene, Meriem; Drubay, Damien; Deutsch, Eric; Barlesi, Fabrice; Planchard, David; Segata, Nicola; Martinez, Stéphanie; Zitvogel, Laurence; Soria, Jean-Charles; Besse, BenjaminDerosa, Lisa; Routy, Bertrand; Thomas, Andrew Maltez; Iebba, Valerio; Zalcman, Gerard; Friard, Sylvie; Mazieres, Julien; Audigier-Valette, Clarisse; Moro-Sibilot, Denis; Goldwasser, François; Silva, Carolina Alves Costa; Terrisse, Safae; Bonvalet, Melodie; Scherpereel, Arnaud; Pegliasco, Hervé; Richard, Corentin; Ghiringhelli, François; Elkrief, Arielle; Desilets, Antoine; Blanc-Durand, Felix; Cumbo, Fabio; Blanco, Aitor; Boidot, Romain; Chevrier, Sandy; Daillère, Romain; Kroemer, Guido; Alla, Laurie; Pons, Nicolas; Le Chatelier, Emmanuelle; Galleron, Nathalie; Roume, Hugo; Dubuisson, Agathe; Bouchard, Nicole; Messaoudene, Meriem; Drubay, Damien; Deutsch, Eric; Barlesi, Fabrice; Planchard, David; Segata, Nicola; Martinez, Stéphanie; Zitvogel, Laurence; Soria, Jean-Charles; Besse, Benjami