IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression.

Aryl hydrocarbon receptor (AHR) activation by tryptophan (Trp) catabolites enhances tumor malignancy and suppresses anti-tumor immunity. The context specificity of AHR target genes has so far impeded systematic investigation of AHR activity and its upstream enzymes across human cancers. A pan-tissue AHR signature, derived by natural language processing, revealed that across 32 tumor entities, interleukin-4-induced-1 (IL4I1) associates more frequently with AHR activity than IDO1 or TDO2, hitherto recognized as the main Trp-catabolic enzymes. IL4I1 activates the AHR through the generation of indole metabolites and kynurenic acid. It associates with reduced survival in glioma patients, promotes cancer cell motility, and suppresses adaptive immunity, thereby enhancing the progression of chronic lymphocytic leukemia (CLL) in mice. Immune checkpoint blockade (ICB) induces IDO1 and IL4I1. As IDO1 inhibitors do not block IL4I1, IL4I1 may explain the failure of clinical studies combining ICB with IDO1 inhibition. Taken together, IL4I1 blockade opens new avenues for cancer therapy.

The eEF2 kinase confers resistance to nutrient deprivation by blocking translation elongation.

Metabolic adaptation is essential for cell survival during nutrient deprivation. We report that eukaryotic elongation factor 2 kinase (eEF2K), which is activated by AMP-kinase (AMPK), confers cell survival under acute nutrient depletion by blocking translation elongation. Tumor cells exploit this pathway to adapt to nutrient deprivation by reactivating the AMPK-eEF2K axis. Adaptation of transformed cells to nutrient withdrawal is severely compromised in cells lacking eEF2K. Moreover, eEF2K knockdown restored sensitivity to acute nutrient deprivation in highly resistant human tumor cell lines. In vivo, overexpression of eEF2K rendered murine tumors remarkably resistant to caloric restriction. Expression of eEF2K strongly correlated with overall survival in human medulloblastoma and glioblastoma multiforme. Finally, C. elegans strains deficient in efk-1, the eEF2K ortholog, were severely compromised in their response to nutrient depletion. Our data highlight a conserved role for eEF2K in protecting cells from nutrient deprivation and in conferring tumor cell adaptation to metabolic stress. PAPERCLIP:

Frequency and Prognostic Value of Circulating Tumor Cells in Cancer of Unknown Primary.

BACKGROUND: Cancer of unknown primary (CUP) is defined as a primary metastatic malignancy, in which the primary tumor remains elusive in spite of a comprehensive diagnostic workup. The frequency and prognostic value of circulating tumor cells (CTCs), which are considered to be the source of metastasis, has not yet been systematically evaluated in CUP. METHODS: A total of 110 patients with a confirmed diagnosis of CUP according to the European Society for Medical Oncology (ESMO) guidelines, who presented to our clinic between July 2021 and May 2023, provided blood samples for CTC quantification using CellSearch methodology. CTC counts were correlated with demographic, clinical, and molecular data generated by comprehensive genomic profiling of tumor tissue. RESULTS: CTCs were detected in 26% of all patients at initial presentation to our department. The highest CTC frequency was observed among patients with unfavorable CUP (35.5%), while patients with single-site/oligometastatic CUP harbored the lowest CTC frequency (11.4%). No statistically significant association between CTC positivity and the number of affected organs (P = 0.478) or disease burden (P = 0.120) was found. High CTC levels (≥5 CTCs/7.5 mL; 12/95 analyzed patients) predicted for adverse overall survival compared to negative or low CTC counts (6-months overall survival rate 90% vs 32%, log-rank P < 0.001; HR 5.43; 95% CI 2.23-13.2). CTC dynamics were also prognostic for overall survival by landmark analysis (log-rank P < 0.001, HR 10.2, 95% CI 1.95-52.9). CONCLUSIONS: CTC frequency is a strong, independent predictor of survival in patients with CUP. CTC quantification provides a useful prognostic tool in the management of these patients.

Weakly Supervised MRI Slice-Level Deep Learning Classification of Prostate Cancer Approximates Full Voxel- and Slice-Level Annotation: Effect of Increasing Training Set Size.

BACKGROUND: Weakly supervised learning promises reduced annotation effort while maintaining performance. PURPOSE: To compare weakly supervised training with full slice-wise annotated training of a deep convolutional classification network (CNN) for prostate cancer (PC). STUDY TYPE: Retrospective. SUBJECTS: One thousand four hundred eighty-nine consecutive institutional prostate MRI examinations from men with suspicion for PC (65 ± 8 years) between January 2015 and November 2020 were split into training (N = 794, enriched with 204 PROSTATEx examinations) and test set (N = 695). FIELD STRENGTH/SEQUENCE: 1.5 and 3T, T2-weighted turbo-spin-echo and diffusion-weighted echo-planar imaging. ASSESSMENT: Histopathological ground truth was provided by targeted and extended systematic biopsy. Reference training was performed using slice-level annotation (SLA) and compared to iterative training utilizing patient-level annotations (PLAs) with supervised feedback of CNN estimates into the next training iteration at three incremental training set sizes (N = 200, 500, 998). Model performance was assessed by comparing specificity at fixed sensitivity of 0.97 [254/262] emulating PI-RADS ≥ 3, and 0.88-0.90 [231-236/262] emulating PI-RADS ≥ 4 decisions. STATISTICAL TESTS: Receiver operating characteristic (ROC) and area under the curve (AUC) was compared using DeLong and Obuchowski test. Sensitivity and specificity were compared using McNemar test. Statistical significance threshold was P = 0.05. RESULTS: Test set (N = 695) ROC-AUC performance of SLA (trained with 200/500/998 exams) was 0.75/0.80/0.83, respectively. PLA achieved lower ROC-AUC of 0.64/0.72/0.78. Both increased performance significantly with increasing training set size. ROC-AUC for SLA at 500 exams was comparable to PLA at 998 exams (P = 0.28). ROC-AUC was significantly different between SLA and PLA at same training set sizes, however the ROC-AUC difference decreased significantly from 200 to 998 training exams. Emulating PI-RADS ≥ 3 decisions, difference between PLA specificity of 0.12 [51/433] and SLA specificity of 0.13 [55/433] became undetectable (P = 1.0) at 998 exams. Emulating PI-RADS ≥ 4 decisions, at 998 exams, SLA specificity of 0.51 [221/433] remained higher than PLA specificity at 0.39 [170/433]. However, PLA specificity at 998 exams became comparable to SLA specificity of 0.37 [159/433] at 200 exams (P = 0.70). DATA CONCLUSION: Weakly supervised training of a classification CNN using patient-level-only annotation had lower performance compared to training with slice-wise annotations, but improved significantly faster with additional training data. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Reproducible Radiomics Features from Multi-MRI-Scanner Test-Retest-Study: Influence on Performance and Generalizability of Models.

BACKGROUND: Radiomics models trained on data from one center typically show a decline of performance when applied to data from external centers, hindering their introduction into large-scale clinical practice. Current expert recommendations suggest to use only reproducible radiomics features isolated by multiscanner test-retest experiments, which might help to overcome the problem of limited generalizability to external data. PURPOSE: To evaluate the influence of using only a subset of robust radiomics features, defined in a prior in vivo multi-MRI-scanner test-retest-study, on the performance and generalizability of radiomics models. STUDY TYPE: Retrospective. POPULATION: Patients with monoclonal plasma cell disorders. Training set (117 MRIs from center 1); internal test set (42 MRIs from center 1); external test set (143 MRIs from center 2-8). FIELD STRENGTH/SEQUENCE: 1.5T and 3.0T; T1-weighted turbo spin echo. ASSESSMENT: The task for the radiomics models was to predict plasma cell infiltration, determined by bone marrow biopsy, noninvasively from MRI. Radiomics machine learning models, including linear regressor, support vector regressor (SVR), and random forest regressor (RFR), were trained on data from center 1, using either all radiomics features, or using only reproducible radiomics features. Models were tested on an internal (center 1) and a multicentric external data set (center 2-8). STATISTICAL TESTS: Pearson correlation coefficient r and mean absolute error (MAE) between predicted and actual plasma cell infiltration. Fisher's z-transformation, Wilcoxon signed-rank test, Wilcoxon rank-sum test; significance level P < 0.05. RESULTS: When using only reproducible features compared with all features, the performance of the SVR on the external test set significantly improved (r = 0.43 vs. r = 0.18 and MAE = 22.6 vs. MAE = 28.2). For the RFR, the performance on the external test set deteriorated when using only reproducible instead of all radiomics features (r = 0.33 vs. r = 0.44, P = 0.29 and MAE = 21.9 vs. MAE = 20.5, P = 0.10). CONCLUSION: Using only reproducible radiomics features improves the external performance of some, but not all machine learning models, and did not automatically lead to an improvement of the external performance of the overall best radiomics model. TECHNICAL EFFICACY: Stage 2.

Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms.

OBJECTIVES: Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI using the prostate imaging reporting and data system (PI-RADS). Fully-automated deep learning (DL) analyzes MRI data independently, and has been shown to be on par with clinical radiologists, but has yet to be incorporated into RCs. The goal of this study is to re-assess the diagnostic quality of RCs, the impact of replacing PI-RADS with DL predictions, and potential performance gains by adding DL besides PI-RADS. MATERIAL AND METHODS: One thousand six hundred twenty-seven consecutive examinations from 2014 to 2021 were included in this retrospective single-center study, including 517 exams withheld for RC testing. Board-certified radiologists assessed PI-RADS during clinical routine, then systematic and MRI/Ultrasound-fusion biopsies provided histopathological ground truth for significant prostate cancer (sPC). nnUNet-based DL ensembles were trained on biparametric MRI predicting the presence of sPC lesions (UNet-probability) and a PI-RADS-analogous five-point scale (UNet-Likert). Previously published RCs were validated as is; with PI-RADS substituted by UNet-Likert (UNet-Likert-substituted RC); and with both UNet-probability and PI-RADS (UNet-probability-extended RC). Together with a newly fitted RC using clinical data, PI-RADS and UNet-probability, existing RCs were compared by receiver-operating characteristics, calibration, and decision-curve analysis. RESULTS: Diagnostic performance remained stable for UNet-Likert-substituted RCs. DL contained complementary diagnostic information to PI-RADS. The newly-fitted RC spared 49% [252/517] of biopsies while maintaining the negative predictive value (94%), compared to PI-RADS ≥ 4 cut-off which spared 37% [190/517] (p < 0.001). CONCLUSIONS: Incorporating DL as an independent diagnostic marker for RCs can improve patient stratification before biopsy, as there is complementary information in DL features and clinical PI-RADS assessment. CLINICAL RELEVANCE STATEMENT: For patients with positive prostate screening results, a comprehensive diagnostic workup, including prostate MRI, DL analysis, and individual classification using nomograms can identify patients with minimal prostate cancer risk, as they benefit less from the more invasive biopsy procedure. KEY POINTS: The current MRI-based nomograms result in many negative prostate biopsies. The addition of DL to nomograms with clinical data and PI-RADS improves patient stratification before biopsy. Fully automatic DL can be substituted for PI-RADS without sacrificing the quality of nomogram predictions. Prostate nomograms show cancer detection ability comparable to previous validation studies while being suitable for the addition of DL analysis.

Onset Time and Characteristics of Postprocedural Bleeding after Endoscopic Resection of Colorectal Lesions: A Multicenter Retrospective Study.

INTRODUCTION: Postprocedural bleeding is a major adverse event after endoscopic resection of colorectal lesions, but the optimal surveillance time after endoscopy is unclear. In this study, we determined onset time and characteristics of postprocedural bleeding events. METHODS: We retrospectively screened patients who underwent endoscopic resection of colorectal lesions at three German hospitals between 2010 and 2019 for postprocedural bleeding events using billing codes. Only patients who required re-endoscopy were included for analysis. For identified patients, we collected demographic data, clinical courses, characteristics of colorectal lesions, and procedure-related variables. Factors associated with late-onset bleeding were determined by univariate and multivariate logistic regression analysis. RESULTS: From a total of 6,820 patients with eligible billing codes, we identified 113 cases with postprocedural bleeding after endoscopic mucosal (61.9%) or snare resection (38.1%) that required re-endoscopy. The median size of the culprit lesion was 20 mm (interquartile range 14-30 mm). The median onset time of postprocedural bleeding was day 3 (interquartile range: 1-6.5 days), with 48.7% of events occurring within 48 h. Multivariate logistic regression analysis demonstrates that a continued intake of antiplatelet drugs (OR: 3.98, 95% CI: 0.89-10.12, p = 0.025) and a flat morphology of the colorectal lesion (OR: 2.98, 95% CI: 1.08-8.01, p = 0.031) were associated with an increased risk for late postprocedural bleeding (>48 h), whereas intraprocedural bleeding was associated with a decreased risk (OR: 0.12, 95% CI: 0.04-0.50, p = 0.001). CONCLUSION: Significant postprocedural bleeding can occur up to 18 days after endoscopic resection of colorectal lesions, but was predominantly observed within 48 h. Continued intake of antiplatelet drugs and a flat polyp morphology are associated with risk for late postprocedural bleeding.

Molecular Long-Term Analysis of the GMMG-HD4 Trial in Multiple Myeloma-Patterns of Association of Chromosomal Aberrations with Response and Proliferation Determining Survival in Selecting Treatments in View of Limited Resources in Low- and Middle-Income Countries.

Based on the lack of differences in progression-free and overall survival after a median follow-up of 93 months in our HOVON-65/GMMG-HD4 trial (German part; n = 395) randomizing VAD induction (vincristin/adriamycin/dexamthasone)/tandem-transplantation/thalidomide-maintenance vs. PAD induction (bortezomib/adriamycin/dexamethasone)/tandem transplantation/bortezomib maintenance, we discern how chromosomal aberrations determine long-term prognosis by different patterns of association with proliferation and treatment-dependent response, whether responses achieved by different regimens are equal regarding prognosis, and whether subpopulations of patients could be defined as treatable without upfront "novel agents" in cases of limited resources, e.g., in low- or middle-income countries. Serum parameters and risk factors were assessed in 395 patients. CD138-purified plasma cells were subjected to fluorescence in situ hybridization (n = 354) and gene expression profiling (n = 204). We found chromosomal aberrations to be associated in four patterns with survival, proliferation, and response: deletion (del) del17p13, del8p21, del13q14, (gain) 1q21+, and translocation t(4;14) (all adverse) associate with higher proliferation. Of these, del17p is associated with an adverse response (pattern 1), and 1q21+, t(4;14), and del13q14 with a treatment-dependent better response (pattern 2). Hyperdiploidy associates with lower proliferation without impacting response or survival (pattern 3). Translocation t(11;14) has no association with survival but a treatment-dependent adverse response (pattern 4). Significantly fewer patients reach a near-complete response or better with "conventional" (VAD) vs. bortezomib-based treatment after induction or high-dose melphalan. These patients, however, show significantly better median progression-free and overall survival. Molecularly, patients responding to the two regimens differ in gene expression, indicating distinct biological properties of the responding myeloma cells. Patients with normal renal function (89.4%), low cytogenetic risk (72.5%), or low proliferation rate (37.9%) neither benefit in progression-free nor overall survival from bortezomib-based upfront treatment. We conclude that response level, the treatment by which it is achieved, and molecular background determine long-term prognosis. Chromosomal aberrations are associated in four patterns with proliferation and treatment-dependent responses. Associations with faster and deeper responses can be deceptive in the case of prognostically adverse aberrations 1q21+ and t(4;14). Far from advocating a return to "outdated" treatments, if resources do not permit state-of-the-art-treatment, normal renal function and/or molecular profiling identifies patient subpopulations doing well without upfront "novel agents".

DNA methylation biomarkers for noninvasive detection of triple-negative breast cancer using liquid biopsy.

Noninvasive detection of aberrant DNA methylation could provide invaluable biomarkers for earlier detection of triple-negative breast cancer (TNBC) which could help clinicians with easier and more efficient treatment options. We evaluated genome-wide DNA methylation data derived from TNBC and normal breast tissues, peripheral blood of TNBC cases and controls and reference samples of sorted blood and mammary cells. Differentially methylated regions (DMRs) between TNBC and normal breast tissues were stringently selected, verified and externally validated. A machine-learning algorithm was applied to select the top DMRs, which then were evaluated on plasma-derived circulating cell-free DNA (cfDNA) samples of TNBC patients and healthy controls. We identified 23 DMRs accounting for the methylation profile of blood cells and reference mammary cells and then selected six top DMRs for cfDNA analysis. We quantified un-/methylated copies of these DMRs by droplet digital PCR analysis in a plasma test set from TNBC patients and healthy controls and confirmed our findings obtained on tissues. Differential cfDNA methylation was confirmed in an independent validation set of plasma samples. A methylation score combining signatures of the top three DMRs overlapping with the SPAG6, LINC10606 and TBCD/ZNF750 genes had the best capability to discriminate TNBC patients from controls (AUC = 0.78 in the test set and AUC = 0.74 in validation set). Our findings demonstrate the usefulness of cfDNA-based methylation signatures as noninvasive liquid biopsy markers for the diagnosis of TNBC.

Contribution of Dynamic Contrast-enhanced and Diffusion MRI to PI-RADS for Detecting Clinically Significant Prostate Cancer.

Background Prostate Imaging Reporting and Data System (PI-RADS) version 2.0 requires multiparametric MRI of the prostate, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging sequences; however, the contribution of DCE imaging remains unclear. Purpose To assess whether DCE imaging in addition to apparent diffusion coefficient (ADC) and normalized T2 values improves PI-RADS version 2.0 for prediction of clinically significant prostate cancer (csPCa). Materials and Methods In this retrospective study, clinically reported PI-RADS lesions in consecutive men who underwent 3-T multiparametric MRI (T2-weighted, DWI, and DCE MRI) from May 2015 to September 2016 were analyzed quantitatively and compared with systematic and targeted MRI-transrectal US fusion biopsy. The normalized T2 signal (nT2), ADC measurement, mean early-phase DCE signal (mDCE), and heuristic DCE parameters were calculated. Logistic regression analysis indicated the most predictive DCE parameters for csPCa (Gleason grade group ≥2). Receiver operating characteristic parameter models were compared using the Obuchowski test. Recursive partitioning analysis determined ADC and mDCE value ranges for combined use with PI-RADS. Results Overall, 260 men (median age, 64 years [IQR, 58-69 years]) with 432 lesions (csPCa [n = 152] and no csPCa [n = 280]) were included. The mDCE parameter was predictive of csPCa when accounting for the ADC and nT2 parameter in the peripheral zone (odds ratio [OR], 1.76; 95% CI: 1.30, 2.44; P = .001) but not the transition zone (OR, 1.17; 95% CI: 0.81, 1.69; P = .41). Recursive partitioning analysis selected an ADC cutoff of 0.897 × 10-3 mm2/sec (P = .04) as a classifier for peripheral zone lesions with a PI-RADS score assessed on the ADC map (hereafter, ADC PI-RADS) of 3. The mDCE parameter did not differentiate ADC PI-RADS 3 lesions (P = .11), but classified lesions with ADC PI-RADS scores greater than 3 with low ADC values (less than 0.903 × 10-3 mm2/sec, P < .001) into groups with csPCa rates of 70% and 97% (P = .008). A lesion size cutoff of 1.5 cm and qualitative DCE parameters were not defined as classifiers according to recursive partitioning (P > .05). Conclusion Quantitative or qualitative dynamic contrast-enhanced MRI was not relevant for Prostate Imaging Reporting and Data System (PI-RADS) 3 lesion risk stratification, while quantitative apparent diffusion coefficient (ADC) values were helpful in upgrading PI-RADS 3 and PI-RADS 4 lesions. Quantitative ADC measurement may be more important for risk stratification than current methods in future versions of PI-RADS. © RSNA, 2022 Online supplemental material is available for this article See also the editorial by Goh in this issue.

Class I HDAC inhibition reduces DNA damage repair capacity of MYC-amplified medulloblastoma cells.

PURPOSE: MYC-driven Group 3 medulloblastoma (MB) (subtype II) is a highly aggressive childhood brain tumor. Sensitivity of MYC-driven MB to class I histone deacetylase inhibitors (HDACi) has been previously demonstrated in vitro and in vivo. In this study we characterize the transcriptional effects of class I HDACi in MYC-driven MB and explore beneficial drug combinations. METHODS: MYC-amplified Group 3 MB cells (HD-MB03) were treated with class I HDACi entinostat. Changes in the gene expression profile were quantified on a microarray. Bioinformatic assessment led to the identification of pathways affected by entinostat treatment. Five drugs interfering with these pathways (olaparib, idasanutlin, ribociclib, selinexor, vinblastine) were tested for synergy with entinostat in WST-8 metabolic activity assays in a 5 × 5 combination matrix design. Synergy was validated in cell count and flow cytometry experiments. The effect of entinostat and olaparib on DNA damage was evaluated by γH2A.X quantification in immunoblotting, fluorescence microscopy and flow cytometry. RESULTS: Entinostat treatment changed the expression of genes involved in 22 pathways, including downregulation of DNA damage response. The PARP1 inhibitors olaparib and pamiparib showed synergy with entinostat selectively in MYC-amplified MB cells, leading to increased cell death, decreased viability and increased formation of double strand breaks, as well as increased sensitivity to additional induction of DNA damage by doxorubicin. Non-MYC-amplified MB cells and normal human fibroblasts were not susceptible to this triple treatment. CONCLUSION: Our study identifies the combination of entinostat with olaparib as a new potential therapeutic approach for MYC-driven Group 3 MB.

Class I HDAC inhibitor entinostat synergizes with PLK1 inhibitors in MYC-amplified medulloblastoma cells.

PURPOSE: We and others have demonstrated that MYC-amplified medulloblastoma (MB) cells are susceptible to class I histone deacetylase inhibitor (HDACi) treatment. However, single drug treatment with HDACi has shown limited clinical efficacy. We hypothesized that addition of a second compound acting synergistically with HDACi may enhance efficacy. METHODS: We used a gene expression dataset to identify PLK1 as a second target in MB cells and validated the relevance of PLK1 in MB. We measured cell metabolic activity, viability, and cycle progression in MB cells after treatment with PLK1-specific inhibitors (PLK1i). Chou-Talalay synergy calculations were used to determine the nature of class I HDACi entinostat and PLK1i interaction which was validated. Finally, the clinical potential of the combination was assessed in the in vivo experiment. RESULTS: MYC-amplified tumor cells are highly sensitive towards treatment with ATP-competitive PLK1i as a monotherapy. Entinostat and PLK1i in combination act synergistically in MYC-driven MB cells, exerting cytotoxic effects at clinically relevant concentrations. The downstream effect is exerted via MYC-related pathways, pointing out the potential of MYC amplification as a clinically feasible predictive biomarker for patient selection. While entinostat significantly extended survival of mice implanted with orthotopic MYC-amplified MB PDX, there was no evidence of the improvement of survival when treating the animals with the combination. CONCLUSION: The combination of entinostat and PLK1i showed synergistic interaction in vitro, but not in vivo. Therefore, further screening of blood-brain barrier penetrating PLK1i is warranted to determine the true potential of the combination as no on-target activity was observed after PLK1i volasertib treatment in vivo.

Application of a validated prostate MRI deep learning system to independent same-vendor multi-institutional data: demonstration of transferability.

OBJECTIVES: To evaluate a fully automatic deep learning system to detect and segment clinically significant prostate cancer (csPCa) on same-vendor prostate MRI from two different institutions not contributing to training of the system. MATERIALS AND METHODS: In this retrospective study, a previously bi-institutionally validated deep learning system (UNETM) was applied to bi-parametric prostate MRI data from one external institution (A), a PI-RADS distribution-matched internal cohort (B), and a csPCa stratified subset of single-institution external public challenge data (C). csPCa was defined as ISUP Grade Group ≥ 2 determined from combined targeted and extended systematic MRI/transrectal US-fusion biopsy. Performance of UNETM was evaluated by comparing ROC AUC and specificity at typical PI-RADS sensitivity levels. Lesion-level analysis between UNETM segmentations and radiologist-delineated segmentations was performed using Dice coefficient, free-response operating characteristic (FROC), and weighted alternative (waFROC). The influence of using different diffusion sequences was analyzed in cohort A. RESULTS: In 250/250/140 exams in cohorts A/B/C, differences in ROC AUC were insignificant with 0.80 (95% CI: 0.74-0.85)/0.87 (95% CI: 0.83-0.92)/0.82 (95% CI: 0.75-0.89). At sensitivities of 95% and 90%, UNETM achieved specificity of 30%/50% in A, 44%/71% in B, and 43%/49% in C, respectively. Dice coefficient of UNETM and radiologist-delineated lesions was 0.36 in A and 0.49 in B. The waFROC AUC was 0.67 (95% CI: 0.60-0.83) in A and 0.7 (95% CI: 0.64-0.78) in B. UNETM performed marginally better on readout-segmented than on single-shot echo-planar-imaging. CONCLUSION: For same-vendor examinations, deep learning provided comparable discrimination of csPCa and non-csPCa lesions and examinations between local and two independent external data sets, demonstrating the applicability of the system to institutions not participating in model training. CLINICAL RELEVANCE STATEMENT: A previously bi-institutionally validated fully automatic deep learning system maintained acceptable exam-level diagnostic performance in two independent external data sets, indicating the potential of deploying AI models without retraining or fine-tuning, and corroborating evidence that AI models extract a substantial amount of transferable domain knowledge about MRI-based prostate cancer assessment. KEY POINTS: • A previously bi-institutionally validated fully automatic deep learning system maintained acceptable exam-level diagnostic performance in two independent external data sets. • Lesion detection performance and segmentation congruence was similar on the institutional and an external data set, as measured by the weighted alternative FROC AUC and Dice coefficient. • Although the system generalized to two external institutions without re-training, achieving expected sensitivity and specificity levels using the deep learning system requires probability thresholds to be adjusted, underlining the importance of institution-specific calibration and quality control.

Prognostic impact of copy number alterations and tumor mutational burden in carcinoma of unknown primary.

INTRODUCTION: Chromosomal aberrations are known to drive metastatic spread, but their profile is still elusive in carcinoma of unknown primary (CUP). Therefore, the aim of this study was to characterize the chromosomal aberration pattern in CUP depending on histological and clinical features and to assess its prognostic impact together with chromothripsis, tumor mutational burden (TMB), microsatellite instability (MSI), and mutational profiles as potential prognostic biomarkers. METHODS: Chromosomal aberrations and chromothripsis were detected by methylation-based copy number variation (CNV) analysis, whereas TMB and MSI were calculated based on large next-generation sequencing (NGS) panels. Putative primaries were assigned by consensus between two independent oncologists. RESULTS: CNV losses varied depending on putative primaries and were more abundant in patients harboring TP53 mutations and/or deletions 17p. CNV loss was prognostically adverse in localized CUP treated with surgery and/or radiotherapy, but not in disseminated poor-risk CUP treated with palliative chemotherapy. CNV loss also worsened the prognosis in squamous cell CUP. Chromothripsis was detected in 18/59 (30.5%) patients without prognostic effect. TMB was highest in cases with MSI, squamous cell histology, and with lung, anal or cervical putative primaries. CONCLUSION: Overall, CNV, chromothripsis, TMB, and MSI profiles in CUP are reminiscent of biological characteristics known from other cancer entities without a unifying CUP-specific signature. Markedly, high-level CNV loss is an adverse predictive biomarker in localized but not disseminated chemotherapy-treated CUP. This implies that chromosomal losses drive CUP progression, but also increase susceptibility to chemotherapy, with both effects apparently leveling out in disseminated CUP.

Whole-body magnetic resonance imaging plus serological follow-up for early identification of progression in smouldering myeloma patients to prevent development of end-organ damage.

The definition of multiple myeloma (MM) was updated in 2014, with the intent to enable earlier treatment and thereby avoid appearance of end-organ damage at progression from smouldering multiple myeloma (SMM) to MM. The purpose of this study was to investigate to which extent the development of end-organ damage at progression to MM was reduced under the updated guidelines. In this prospective observational cohort study (ClinicalTrials.gov Identifier: NCT01374412), between 2014 and 2020, 96 SMM patients prospectively underwent whole-body magnetic resonance imaging (wb-MRI) and serological follow-up at baseline and every 6 months thereafter. A total of 22 patients progressed into MM during follow-up, of which seven (32%) showed SLiM-criteria only but no end-organ damage. Four (57%) of the seven patients who progressed by SLiM-criteria only progressed with >1 focal lesion (FL) or a growing FL, and three (43%) due to serum free light-chain-ratio ≥100. Fifteen (68%) out of 22 patients who progressed still suffered from end-organ damage at progression. The updated disease definition reduced the proportion of SMM patients suffering from end-organ damage at progression to MM by one third. wb-MRI is an important tool for detection of SMM patients who progress to MM without end-organ damage.

Integrated clinicomolecular characterization identifies RAS activation and CDKN2A deletion as independent adverse prognostic factors in cancer of unknown primary.

Cancer of unknown primary (CUP) denotes a malignancy with histologically confirmed metastatic spread while the primary tumor remains elusive. Here, we address prognostic and therapeutic implications of mutations and copy number variations (CNVs) detected in tumor tissue in the context of a comprehensive clinical risk assessment. Targeted panel sequencing was performed in 252 CUP patients. 71.8% of patients had unfavorable CUP according to ESMO guidelines. 74.7% were adeno- and 13.7% squamous cell carcinomas. DNA was extracted from microdissected formalin-fixed, paraffin-embedded tissues. For library preparation, mostly multiplex PCR-based Ion Torrent AmpliSeq™ technology with Oncomine comprehensive assays was used. Most frequent genetic alterations were mutations/deletions of TP53 (49.6%), CDKN2A (19.0%) and NOTCH1 (14.1%) as well as oncogenic activation of KRAS (23.4%), FGFR4 (14.9%) and PIK3CA (10.7%). KRAS activation was predominantly found in adenocarcinomas (p = 0.01), PIK3CA activation in squamous cell carcinomas (p = 0.03). Male sex, high ECOG score, unfavorable CUP, higher number of involved organs and RAS activation predicted decreased event-free and overall survival in multivariate analysis. Deletions of CDKN2A were prognostically adverse regarding overall survival. TP53 mutations did not significantly influence prognosis in the overall cohort, but worsened prognosis in otherwise favorable CUP subtypes. Although not standard in CUP, for 17/198 (8.6%) patients molecularly targeted treatment was recommended and 10 patients (5.1%) were treated accordingly. In conclusion, besides the identification of drug targets, panel sequencing in CUP is prognostically relevant, with RAS activation and CDKN2A deletion emerging as novel independent risk factors in a comprehensive assessment with clinicopathological data.

Response Improvement Rather than Response Status after First Autologous Stem Cell Transplantation Is a Significant Prognostic Factor for Survival Benefit from Tandem Compared with Single Transplantation in Multiple Myeloma Patients.

High-dose chemotherapy and autologous stem cell transplantation (ASCT) have provided effective treatment for patients with newly diagnosed multiple myeloma for more than 3 decades; however, which patients will benefit from tandem ASCT compared with single ASCT remains unclear. Here we retrospectively analyzed 978 trial and nontrial patients who underwent single or tandem ASCT in Heidelberg or other German-Speaking Myeloma Multicenter Group centers. Our results show that response improvement after first ASCT is a significant prognostic factor for progression-free survival benefit from tandem versus single ASCT (multivariable analysis, P = .002; hazard ratio, .64; 95% confidence interval, .48 to .85; P for interaction = .02). The depth of response after first ASCT and the cytogenetic profile did not have a significant prognostic effect on survival benefit from tandem ASCT. Our results suggest that it is not the response depth, but rather the response improvement after first ASCT is of prognostic significance regarding the benefit of tandem ASCT versus single ASCT.

T-type calcium channel inhibition restores sensitivity to MAPK inhibitors in de-differentiated and adaptive melanoma cells.

BACKGROUND: Drug resistance remains as one of the major challenges in melanoma therapy. It is well known that tumour cells undergo phenotypic switching during melanoma progression, increasing melanoma plasticity and resistance to mitogen-activated protein kinase inhibitors (MAPKi). METHODS: We investigated the melanoma phenotype switching using a partial reprogramming model to de-differentiate murine melanoma cells and target melanoma therapy adaptation against MAPKi. RESULTS: Here, we show that partially reprogrammed cells are a less proliferative and more de-differentiated cell population, expressing a gene signature for stemness and suppressing melanocyte-specific markers. To investigate adaptation to MAPKi, cells were exposed to B-Raf Proto-Oncogene (BRAF) and mitogen-activated protein kinase kinase (MEK) inhibitors. De-differentiated cells became less sensitive to MAPKi, showed increased cell viability and decreased apoptosis. Furthermore, T-type calcium channels expression increased in adaptive murine cells and in human adaptive melanoma cells. Treatment with the calcium channel blocker mibefradil induced cell death, differentiation and susceptibility to MAPKi in vitro and in vivo. CONCLUSION: In summary, we show that partial reprogramming of melanoma cells induces de-differentiation and adaptation to MAPKi. Moreover, we postulated a calcium channel blocker such as mibefradil, as a potential candidate to restore sensitivity to MAPKi in adaptive melanoma cells.

cMyc and ERK activity are associated with resistance to ALK inhibitory treatment in glioblastoma.

BACKGROUND: Anaplastic lymphoma kinase (ALK) is expressed in ~ 60% of glioblastomas and conveys tumorigenic functions. Therefore, ALK inhibitory strategies with alectinib are conceivable for patients with glioblastoma. The aims of this preclinical study were to investigate efficacy as well as to understand and potentially overcome primary and acquired resistance mechanisms of alectinib in glioblastoma. METHODS: Efficacy of alectinib was analyzed dependent on ALK expression in different glioblastoma initiating cells and after lentiviral knockdown of ALK. Alectinib resistant cells were generated by continuous treatment with increasing alectinib doses over 3 months. M-RNA, phospho-protein and protein regulation were analyzed to decipher relevant pathways associated to treatment or resistance and specifically inhibited to evaluate rational salvage therapies. RESULTS: Alectinib reduced clonogenicity and proliferation and induced apoptosis in ALK expressing glioblastoma initiating cells, whereas cells without ALK expression or after ALK depletion via knockdown showed primary resistance against alectinib. High expression of cMyc and activation of the ERK1/2 pathway conferred resistance against alectinib in ALK expressing glioblastoma cells. Pharmacological inhibition of these pathways by cMyc inhibitor or MEK inhibitor, trametinib, overcame alectinib resistance and re-sensitized resistant cells to continued alectinib treatment. The combination of alectinib with radiotherapy demonstrated synergistic effects in inhibition of clonogenicity in non-resistant and alectinib resistant glioblastoma cells. CONCLUSION: The data offer rationales for alectinib treatment in ALK expressing glioblastoma and for the use of ALK expression status as potential biomarker for alectinib treatment. In addition, the results propose MEK inhibition or radiotherapy as reasonable salvage treatments after acquired alectinib resistance.

Cell competition is a tumour suppressor mechanism in the thymus.

Cell competition is an emerging principle underlying selection for cellular fitness during development and disease. Competition may be relevant for cancer, but an experimental link between defects in competition and tumorigenesis is elusive. In the thymus, T lymphocytes develop from precursors that are constantly replaced by bone-marrow-derived progenitors. Here we show that in mice this turnover is regulated by natural cell competition between 'young' bone-marrow-derived and 'old' thymus-resident progenitors that, although genetically identical, execute differential gene expression programs. Disruption of cell competition leads to progenitor self-renewal, upregulation of Hmga1, transformation, and T-cell acute lymphoblastic leukaemia (T-ALL) resembling the human disease in pathology, genomic lesions, leukaemia-associated transcripts, and activating mutations in Notch1. Hence, cell competition is a tumour suppressor mechanism in the thymus. Failure to select fit progenitors through cell competition may explain leukaemia in X-linked severe combined immune deficiency patients who showed thymus-autonomous T-cell development after therapy with gene-corrected autologous progenitors.