[Novel therapies for multiple myeloma].

B-cell maturation antigen (BCMA)-targeting therapy is the most common approach to immunotherapy and cellular therapy for multiple myeloma (MM). Three major agents, CAR-T cells, bispecific antibodies, and ADC have been developed as novel therapeutic agents. CAR-T therapy showed favorable efficacy in the treatment of relapsed and refractory MM (RR MM) and was tried in early lines of therapy. Similarly, bispecific antibodies targeting BCMA or other targets have also shown promising effects in treatment of RR MM, and have been now tested in combination with other agents. Although issues such as poor fitness or exhaustion of T cells and increased susceptibility to viral infection remain to be fully resolved, novel immunotherapies and cellular therapies should further improve the prognosis of patients with RR MM.

Antibody-Drug Conjugates in Urothelial Cancer: From Scientific Rationale to Clinical Development.

Antibody-drug conjugates (ADCs) have been a significant advancement in cancer therapy, particularly for urothelial cancer (UC). These innovative treatments, originally developed for hematological malignancies, use target-specific monoclonal antibodies linked to potent cytotoxic agents. This rational drug design efficiently delivers cancer cell-killing agents to cells expressing specific surface proteins, which are abundant in UC owing to their high antigen expression. UC is an ideal candidate for ADC therapy, as it enhances on-target efficacy while mitigating systemic toxicity. In recent years, considerable progress has been made in understanding the biology and mechanisms of tumor progression in UC. However, despite the introduction of immune checkpoint inhibitors, advanced UC is characterized by rapid progression and poor survival rates. Targeted therapies that have been developed include the anti-nectin 4 ADC enfortumab vedotin and the fibroblast growth factor receptor inhibitor erdafitinib. Enfortumab vedotin has shown efficacy in prospective studies in patients with advanced UC, alone and in combination with pembrolizumab. The anti-Trop-2 ADC sacituzumab govitecan has also demonstrated effectiveness in single-armed studies. This review highlights the mechanism of action of ADCs, their application in mono- and combination therapies, primary mechanisms of resistance, and future perspectives for their clinical use in UC treatment. ADCs have proven to be an increasingly vital component of the therapeutic landscape for urothelial carcinoma, filling a gap in the treatment of this progressive disease.

The Use of Apparent Diffusion Coefficient Values for Differentiating Bevacizumab-Related Cytotoxicity from Tumor Recurrence and Radiation Necrosis in Glioblastoma.

OBJECTIVES: Glioblastomas (GBM) are the most common primary invasive neoplasms of the brain. Distinguishing between lesion recurrence and different types of treatment related changes in patients with GBM remains challenging using conventional MRI imaging techniques. Therefore, accurate and precise differentiation between true progression or pseudoresponse is crucial in deciding on the appropriate course of treatment. This retrospective study investigated the potential of apparent diffusion coefficient (ADC) map values derived from diffusion-weighted imaging (DWI) as a noninvasive method to increase diagnostic accuracy in treatment response. METHODS: A cohort of 21 glioblastoma patients (mean age: 59.2 ± 11.8, 12 Male, 9 Female) that underwent treatment with bevacizumab were selected. The ADC values were calculated from the DWI images obtained from a standardized brain protocol across 1.5-T and 3-T MRI scanners. Ratios were calculated for rADC values. Lesions were classified as bevacizumab-induced cytotoxicity based on characteristic imaging features (well-defined regions of restricted diffusion with persistent diffusion restriction over the course of weeks without tissue volume loss and absence of contrast enhancement). The rADC value was compared to these values in radiation necrosis and recurrent lesions, which were concluded in our prior study. The nonparametric Wilcoxon signed rank test with p < 0.05 was used for significance. RESULTS: The mean ± SD age of the selected patients was 59.2 ± 11.8. ADC values and corresponding mean rADC values for bevacizumab-induced cytotoxicity were 248.1 ± 67.2 and 0.39 ± 0.10, respectively. These results were compared to the ADC values and corresponding mean rADC values of tumor progression and radiation necrosis. Significant differences between rADC values were observed in all three groups (p < 0.001). Bevacizumab-induced cytotoxicity had statistically significant lower ADC values compared to both tumor recurrence and radiation necrosis. CONCLUSION: The study demonstrates the potential of ADC values as noninvasive imaging biomarkers for differentiating recurrent glioblastoma from radiation necrosis and bevacizumab-induced cytotoxicity.

Design and synthesis of novel site-specific antibody-drug conjugates that target TROP2.

The approval of Trodelvy® validates TROP2 as a druggable but challenging target for antibody-drug conjugates (ADCs) to treat metastatic triple-negative breast cancer (mTNBC). Here, based on the TROP2-targeted antibody sacituzumab, we designed and developed several site-specific ADC candidates, which employ MMAE (monomethyl auristatin E) as the toxin, via IgG glycoengineering or affinity-directed traceless conjugation. Systematic evaluation of these site-specific ADCs in homogeneity, hydrophilicity, stability, and antitumor efficiency was conducted. The results indicate that the site-specific ADCs gsADC 3b made from one-step glycoengineering exhibit good aggregation stability and in vivo efficacy, providing a new format of ADCs that target TROP2.

A 9-10-Bit Adjustable and Energy-Efficient Switching Scheme for Successive Approximation Register Analog-to-Digital Converter with One Least Significant Bit Common-Mode Voltage Variation.

A 9-10-bit adjustable and energy-efficient switching scheme for SAR ADC with one-LSB common-mode voltage variation is proposed. Based on capacitor-splitting technology and common-mode conversion techniques, the proposed switching scheme reduces the DAC switching energy by 96.41% compared to the conventional scheme. The low complexity and the one-LSB common-mode voltage offset of this scheme benefit from the simultaneous switching of the reference voltages of the capacitors corresponding to the positive array and the negative array throughout the entire reference voltage switching process, and the reference voltage of each capacitor in the scheme does not change more than two voltages. The post-layout result shows that the ADC achieves the 54.96 dB SNDR, the 61.73 dB SFDR, and the 0.67 µw power consumption with the 10-bit mode and the 48.33 dB SNDR, the 54.17 dB SFDR, and the 0.47 µw power consumption with the 9-bit mode in a 180 nm process with a 100 kS/s sampling frequency.

A 14-Bit Hybrid Analog-to-Digital Converter for Infrared Focal Plane Array Digital Readout Integrated Circuit.

This paper presents a 14-bit hybrid column-parallel compact analog-to-digital converter (ADC) for the application of digital infrared focal plane arrays (IRFPAs) with compromised power and speed performance. The proposed hybrid ADC works in two phases: in the first phase, a 7-bit successive approximation register (SAR) ADC performs coarse quantization; in the second phase, a 7-bit single-slope (SS) ADC performs fine quantization to complete the residue voltage conversion. In this work, the number of unit capacitors is reduced to 1/128th of that of a conventional 14-bit SAR ADC, which is beneficial for the application of small pixel-pitch IRFPAs. In this work, a tradeoff segmented thermometer-coded digital-to-analog converter (DAC) is adopted in the first 7-bit coarse quantization process: the lower 3-bit is binary coded, and the upper 4-bit is thermometer coded. A thermometer-coded DAC can improve the linearity of ADC. Capacitor array matching can be incredibly relaxed compared with a binary-weight 14-bit SAR ADC, resulting in a noncalibration feature. Moreover, by sharing DAC and comparator analog circuits between the SAR ADC and the SS ADC, the power consumption and layout area are consequently reduced. The proposed hybrid ADC was fabricated using a 180 nm CMOS process. The measurement results show that the proposed ADC has a differential nonlinearity of -0.61/+0.84 LSB and a sampling rate of 120 kS/s. The developed ADC achieves a temporal noise of 1.7 LSBrms at a temperature of 77 K. In addition, the SNDR is 72.9 dB, and the ENOB is 11.82 bit, respectively. Total power consumption is 71 µW from supply voltages of 3.3 V (analog) and 1.8 V (digital).

Homologous recombination proficient subtypes of high-grade serous ovarian cancer: treatment options for a poor prognosis group.

Approximately 50% of tubo-ovarian high-grade serous carcinomas (HGSCs) have functional homologous recombination-mediated (HR) DNA repair, so-called HR-proficient tumors, which are often associated with primary platinum resistance (relapse within six months after completion of first-line therapy), minimal benefit from poly(ADP-ribose) polymerase (PARP) inhibitors, and shorter survival. HR-proficient tumors comprise multiple molecular subtypes including cases with CCNE1 amplification, AKT2 amplification or CDK12 alteration, and are often characterized as "cold" tumors with fewer infiltrating lymphocytes and decreased expression of PD-1/PD-L1. Several new treatment approaches aim to manipulate these negative prognostic features and render HR-proficient tumors more susceptible to treatment. Alterations in multiple different molecules and pathways in the DNA damage response are driving new drug development to target HR-proficient cancer cells, such as inhibitors of the CDK or P13K/AKT pathways, as well as ATR inhibitors. Treatment combinations with chemotherapy or PARP inhibitors and agents targeting DNA replication stress have shown promising preclinical and clinical results. New approaches in immunotherapy are also being explored, including vaccines or antibody drug conjugates. Many approaches are still in the early stages of development and further clinical trials will determine their clinical relevance. There is a need to include HR-proficient tumors in ovarian cancer trials and to analyze them in a more targeted manner to provide further evidence for their specific therapy, as this will be crucial in improving the overall prognosis of HGSC and ovarian cancer in general.

Can initial apparent diffusion coefficient and tumour volume predict future metastases in treatment-naive patients with laryngeal squamous cell carcinoma.

Purpose: To evaluate the predictive capability of the apparent diffusion coefficient (ADC) at initial diagnosis in treatment-naive patients with laryngeal squamous cell carcinoma (LSCC) for the development of future metastases. Material and methods: Magnetic resonance images of patients with pathologically proven non-metastatic, treatmentnaive LSCC were retrospectively evaluated. Follow-up positron emission tomography scans were assessed for the scanning of metastases. Results: A total of 37 patients (32 males and 5 females) with a mean age of 62.8 ± 8.9 years were enrolled. Mean tumour volume and ADC were 4.8 ± 62 cm3 and 0.72 ± 0.51 × 10-3 mm2/s, respectively. Six local and 8 distant metastases were detected in a mean follow-up period of 17.5 ± 10.2 months. A significant association between ADC and the presence distant metastases (p = 0.046) and local metastases (p = 0.042) was found. The difference in mean ADC values between future metastatic and non-metastatic initial tumours was significant (p = 0.017). Conclusions: Pre-treatment ADC values and volume of the initial tumour might provide early information about the development of future metastases in patients with LSCC in this series.

Precise Prostate Cancer Assessment Using IVIM-Based Parametric Estimation of Blood Diffusion from DW-MRI.

Prostate cancer is a significant health concern with high mortality rates and substantial economic impact. Early detection plays a crucial role in improving patient outcomes. This study introduces a non-invasive computer-aided diagnosis (CAD) system that leverages intravoxel incoherent motion (IVIM) parameters for the detection and diagnosis of prostate cancer (PCa). IVIM imaging enables the differentiation of water molecule diffusion within capillaries and outside vessels, offering valuable insights into tumor characteristics. The proposed approach utilizes a two-step segmentation approach through the use of three U-Net architectures for extracting tumor-containing regions of interest (ROIs) from the segmented images. The performance of the CAD system is thoroughly evaluated, considering the optimal classifier and IVIM parameters for differentiation and comparing the diagnostic value of IVIM parameters with the commonly used apparent diffusion coefficient (ADC). The results demonstrate that the combination of central zone (CZ) and peripheral zone (PZ) features with the Random Forest Classifier (RFC) yields the best performance. The CAD system achieves an accuracy of 84.08% and a balanced accuracy of 82.60%. This combination showcases high sensitivity (93.24%) and reasonable specificity (71.96%), along with good precision (81.48%) and F1 score (86.96%). These findings highlight the effectiveness of the proposed CAD system in accurately segmenting and diagnosing PCa. This study represents a significant advancement in non-invasive methods for early detection and diagnosis of PCa, showcasing the potential of IVIM parameters in combination with machine learning techniques. This developed solution has the potential to revolutionize PCa diagnosis, leading to improved patient outcomes and reduced healthcare costs.

The contrast-free diffusion MRI multiple index for the early prediction of pathological response to neoadjuvant chemotherapy in breast cancer.

Early tumor response prediction can help avoid overtreatment with unnecessary chemotherapy sessions. It is important to determine whether multiple apparent diffusion coefficient indices (S index, ADC-diff) are effective in the early prediction of pathological response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Patients with stage II and III BCs who underwent T1WI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI using a 3 T system were included. They were divided into two groups: major histological responders (MHRs, Miller-Payne G4/5) and nonmajor histological responders (nMHRs, Miller-Payne G1-3). Three b values were used for DWI to derive the S index; ADC-diff values were obtained using b = 0 and 1000 s/mm2. The different interquartile ranges of percentile S-index and ADC-diff values after treatment were calculated and compared. The assessment was performed at baseline and after two and four NAC cycles. A total of 59 patients were evaluated. There are some correlations of interquartile ranges of S-index parameters and ADC-diff values with histopathological prognostic factors (such as estrogen receptor and human epidermal growth factor receptor 2 expression, all p < 0.05), but no significant differences were found in some other interquartile ranges of S-index parameters or ADC-diff values between progesterone receptor positive and negative or for Ki-67 tumors (all P > 0.05). No differences were found in the dynamic contrast-enhanced MRI characteristics between the two groups. HER-2 expression and kurtosis of the S-index distribution were screened out as independent risk factors for predicting MHR group (p < 0.05, area under the curve (AUC) = 0.811) before NAC. After early NAC (two cycles), only the 10th percentile S index was statistically significant between the two groups (p < 0.05, AUC = 0.714). No significant differences were found in ADC-diff value at any time point of NAC between the two groups (P > 0.1). These findings demonstrate that the S-index value may be used as an early predictor of pathological response to NAC in BC; the value of ADC-diff as an imaging biomarker of NAC needs to be further confirmed by ongoing multicenter prospective trials.

The value of whole tumor apparent diffusion coefficient histogram parameters in predicting meningiomas progesterone receptor expression.

This letter provides a critical assessment of a previous study on the utility of whole tumor apparent diffusion coefficient (ADC) histogram characteristics in predicting meningioma progesterone receptor expression. While acknowledging the benefits of employing classical diffusion-weighted imaging (DWI) for non-invasive tumor evaluation, it also emphasizes significant drawbacks. Advanced imaging techniques such as diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) were not used in the study, which could have provided a more comprehensive understanding of tumor microstructure and heterogeneity. Furthermore, the inclusion of necrotic and cystic areas in ADC analysis may distort results due to their different diffusion properties. While focusing on first-order ADC histogram characteristics is useful, it ignores the potential insights gained from higher-order features and texture analysis. These limitations indicate that future research should combine improved imaging modalities with thorough analytical methodologies to increase the predictive value of imaging biomarkers for meningioma features and progesterone receptor expression.

Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values.

Background: Distinguishing between prostatic cancer (PCa) and chronic prostatitis (CP) is sometimes challenging, and Gleason grading is strongly associated with prognosis in PCa. The continuous-time random-walk diffusion (CTRW) model has shown potential in distinguishing between PCa and CP as well as predicting Gleason grading. Purpose: This study aimed to quantify the CTRW parameters (α, ß & Dm) and apparent diffusion coefficient (ADC) of PCa and CP tissues; and then assess the diagnostic value of CTRW and ADC parameters in differentiating CP from PCa and low-grade PCa from high-grade PCa lesions. Study type: Retrospective (retrospective analysis using prospective designed data). Population: Thirty-one PCa patients undergoing prostatectomy (mean age 74 years, range 64-91 years), and thirty CP patients undergoing prostate needle biopsies (mean age 68 years, range 46-79 years). Field strength/Sequence: MRI scans on a 3.0T scanner (uMR790, United Imaging Healthcare, Shanghai, China). DWI were acquired with 12 b-values (0, 50, 100, 150, 200, 500, 800, 1200, 1500, 2000, 2500, 3000 s/mm2). Assessment: CTRW parameters and ADC were quantified in PCa and CP lesions. Statistical tests: The Mann-Whitney U test was used to evaluate the differences in CTRW parameters and ADC between PCa and CP, high-grade PCa, and low-grade PCa. Spearman's correlation of the pathologic grading group (GG) with CTRW parameters and ADC was evaluated. The usefulness of CTRW parameters, ADC, and their combinations (Dm, α and ß; Dm, α, ß, and ADC) to differentiate PCa from CP and high-grade PCa from low-grade PCa was determined by logistic regression and receiver operating characteristic curve (ROC) analysis. Delong test was used to compare the differences among AUCs. Results: Significant differences were found for the CTRW parameters (α, Dm) between CP and PCa (all P<0.001), high-grade PCa, and low-grade PCa (α:P=0.024, Dm:P=0.021). GG is correlated with certain CTRW parameters and ADC(α:P<0.001,r=-0.795; Dm:P<0.001,r=-0.762;ADC:P<0.001,r=-0.790). Moreover, CTRW parameters (α, ß, Dm) combined with ADC showed the best diagnostic efficacy for distinguishing between PCa and CP as well as predicting Gleason grading. The differences among AUCs of ADC, CTRW parameters and their combinations were not statistically significant (P=0.051-0.526). Conclusion: CTRW parameters α and Dm, as well as their combination were beneficial to distinguish between CA and PCa, low-grade PCa and high-grade PCa lesions, and CTRW parameters and ADC had comparable diagnostic performance.

Intan Technologies integrated circuits can produce analog-to-digital conversion artifacts that affect neural signal acquisition.

Objective.Intan Technologies' integrated circuits (ICs) are valuable tools for neurophysiological data acquisition, providing signal amplification, filtering, and digitization from many channels (up to 64 channels/chip) at high sampling rates (up to 30 kSPS) within a compact package (⩽9× 7 mm). However, we found that the analog-to-digital converters (ADCs) in the Intan RHD2000 series ICs can produce artifacts in recorded signals. Here, we examine the effects of these ADC artifacts on neural signal quality and describe a method to detect them in recorded data.Approach.We identified two types of ADC artifacts produced by Intan ICs: 1) jumps, resulting from missing output codes, and 2) flatlines, resulting from overrepresented output codes. We identified ADC artifacts in neural recordings acquired with Intan RHD2000 ICs and tested the repeated performance of 17 ICsin vitro. With the on-chip digital-signal-processing disabled, we detected the ADC artifacts in each test recording by examining the distribution of unfiltered ADC output codes.Main Results.We found larger ADC artifacts in recordings using the Intan RHX data acquisition software versions 3.0-3.2, which did not run the necessary ADC calibration command when the inputs to the Intan recording controller were rescanned. This has been corrected in the Intan RHX software version 3.3. We found that the ADC calibration routine significantly reduced, but did not fully eliminate, the occurrence and size of ADC artifacts as compared with recordings acquired when the calibration routine was not run (p< 0.0001). When the ADC calibration routine was run, we found that the artifacts produced by each ADC were consistent over time, enabling us to sort ICs by performance.Significance.Our findings call attention to the importance of evaluating signal quality when acquiring electrophysiological data using Intan Technologies ICs and offer a method for detecting ADC artifacts in recorded data.

Utility of ADC Values for Differentiating Uterine Sarcomas From Leiomyomas: Systematic Review and Meta-Analysis.

Background: Uterine sarcomas are rare; however, they display imaging features that overlap those of leiomyomas. The potential for undetected uterine sarcomas is clinically relevant because minimally invasive treatment of leiomyomas may lead to cancer dissemination. ADC values have shown potential for differentiating benign and malignant uterine masses. Objective: The purpose of this study was to perform a systematic review of the diagnostic performance of ADC values in differentiating uterine sarcomas from leiomyomas. Evidence acquisition: We searched three electronic databases (MEDLINE, EMBASE, and Cochrane databases) for studies distinguishing uterine sarcomas from leiomyomas using MRI, including ADC, with pathologic tissue confirmation or imaging follow-up as the reference standard. Data extraction and QUADAS-2 quality assessment were performed. Sensitivity and specificity were pooled using hierarchic models, including bivariate and hierarchic summary ROC models. Metaregression was used to assess the impact of various factors on heterogeneity. Evidence synthesis: Twenty-one studies met study inclusion criteria. Pooled sensitivity and specificity were 89% (95% CI, 82-94%) and 86% (95% CI, 78-92%), respectively. Area under the summary ROC curve was 94% (95% CI, 92-96%). Context of ADC interpretation (i.e., standalone vs part of multiparametric MRI [mpMRI]) was the only factor found to account significantly for heterogeneity (p = .01). Higher specificity (95% [95% CI, 92-99%] vs 82% [95% CI, 75-89%]) and similar sensitivity (94% [95% CI, 89-99%] vs 88% [95% CI, 82-93%]) were observed when ADC was evaluated among mpMRI features as compared with standalone ADC assessment. ADC cutoff values ranged (0.87-1.29 × 10-3 mm2/s) but were not associated with statistically different performance (p = .37). Pooled mean ADC values in sarcomas and leiomyomas were 0.904 × 10-3 mm2/s and 1.287 × 10-3 mm2/s, respectively. Conclusion: As part of mpMRI evaluation of uterine masses, mass ADC value less than 0.904 × 10-3 mm2/s may be a useful test-positive threshold for uterine sarcoma, consistent with a prior expert consensus statement. Institutional protocols may influence locally selected ADC values. Clinical Impact: Using ADC as part of mpMRI assessment improves detection of uterine sarcoma, which could influence candidate selection for minimally invasive treatments.

Correlation of ADC values of adult brain tumors with the diagnosis and pathological grade: A cross-sectional multicenter study.

Background and Aim: Brain tumors are common, requiring physicians to have a precise understanding of them for accurate diagnosis and treatment. Considering that various histological tumor types present different cellularity, we conducted this research to examine the role of apparent diffusion coefficient (ADC) values in the differential diagnosis and pathologic grading of brain tumor types. Methods: In this cross-sectional study, we gathered pathology reports of histological samples of adult brain tumors. The tissue sample of brain tumors were examined histologically by a pathologist. The magnetic resonance imaging data of these patients were interpreted by a neuroradiologist. The measured ADC values and ADC ratios were calculated. Standard mean ADC values were expressed as 10- 6 mm2/s. The findings were compared according to the histological diagnosis of each tumor. Results: Sixty-eight patients were included in the study: 34 (50%) were male, and 34 (50%) were female. The average age of the patients was 51.69 + 16.40 years. In the examination of tumor type, 16 (23.5%) were astrocytoma, 9 (13.2%) were oligodendroglioma, 20 (29.4%) were glioblastoma, 4 (5.9%) were medulloblastoma, and 19 (27.9%) were metastatic tumors. the average value of ADC was statistically significantly different according to the pathological type of tumor (p < 0.001). The two-by-two comparison of average ADC among tumor types revealed significant differences, except for oligodendroglioma and glioblastoma (p-value = 0.87) and glioblastoma and medulloblastoma (p-value = 0.347). The average value of ADC and ADC ratio was statistically significantly different according to the pathological grade of the tumor (p < 0.001). In the two-by-two comparison of average ADC between all pathological grades of the tumor showed a significance difference except for Grade I and Grade II (p-value = 0.355). The mean value of ADC and ADC ratio for glioblastoma and metastatic tumors showed no significant difference. Conclusion: The assessment of brain tumor grade through ADC examination will help to estimate prognosis and devising suitable therapeutic strategies.

Recent developments and future directions of first-line systemic therapy combined with immunotherapy for advanced or metastatic urothelial carcinoma: a historical perspective on treatment evolution.

Urothelial carcinoma presents significant treatment challenges, especially in advanced stages. Traditionally managed with platinum-based chemotherapy, the advent of immunotherapies, particularly immune checkpoint inhibitors, has revolutionized urothelial carcinoma treatment. This review explores the evolution of urothelial carcinoma management, focusing on the transition from immune checkpoint inhibitors monotherapy to innovative combination therapies. Pembrolizumab, following the KEYNOTE-045 trial, emerged as a pivotal ICI in pretreated metastatic urothelial carcinoma, outperforming traditional chemotherapy. However, limitations surfaced in untreated metastatic urothelial carcinoma patients, particularly in those with low PD-L1 expression, as evidenced by trials like IMvigor130 and KEYNOTE-361. These challenges led to the exploration of combination therapies, including immune checkpoint inhibitors with platinum-based chemotherapy, tyrosine kinase inhibitors, and antibody-drug conjugates. Notably, the CheckMate 901 trial demonstrated improved outcomes with a nivolumab-chemotherapy combination. A significant breakthrough was achieved with the combination of enfortumab vedotin, an antibody-drug conjugates, and pembrolizumab, setting a new standard in first-line treatment for locally advanced or metastatic urothelial carcinoma. Future directions involve further exploration of antibody-drug conjugates and immune checkpoint inhibitors, as seen in the TROPHY-U-01 and TROPiCS-4 trials. The review concludes that the locally advanced or metastatic urothelial carcinoma treatment landscape is rapidly evolving, with combination therapies offering promising avenues for improved patient outcomes, signaling a new era in urothelial carcinoma management.

Bi-Parameter MRI Could Quantitatively Assess the Zonal Heterogeneity of Prostate Cancer.

INTRODUCTION: Prostate cancer (PCa) located in the peripheral zone (PZ) and transitional zone (TZ) showed a different clinical and pathological characteristic. This passage aims to preliminarily evaluate the relationship between the zonal heterogeneity of PCa quantitatively assessed by bpMRI and pathological risk stratification of the primary lesion. METHODS: This prospective study was conducted from January 2019 to February 2023. A total of 113 PCa patients whose bpMRI data indicated that the lesions located in only 1 single zone of the prostate were selected. A transrectal ultrasound and MRI-targeted biopsy were performed to verify the bpMRI results, and then radical prostatectomy (RP) was performed in 3 weeks after the biopsy. The high-risk (HR) group was defined as ISUP grades ≥ 3. Binary regression was performed to evaluate if the zonal heterogeneity could be an independent predictor of the HR group. The receiver operator characteristic (ROC) curve was performed to analyze the added value of zonal location in predicting the HR group. RESULTS: PSA, T staging, and ISUP grades, incidence of positive surgical margins were significantly lower in the TZ PCa, and the ADCmin, and ADCmean values in the TZ PCa were significantly higher (all P < .01). The zonal heterogeneity could independently predict the HR group patients (OR: 5.170 [1.663-16.067], P = .005) and improve the predicting efficiency of HR patients (AUC 0.824, 95% CI, 0.741-0.889). CONCLUSIONS: BpMRI could quantitively assess the zonal heterogeneity of PCa precisely and increase the predicting efficacy of HR patients, which can provide better help for clinical individualized treatment.

Overview of Systemic Therapies in Penile Cancer.

Penile cancer (PC), although rare, poses significant challenges in both diagnosis and treatment. Penile squamous cell carcinoma (PSCC) represents the most common histologic subtype of PC, accounting for approximately 95% of cases. With limited therapeutic options available, systemic therapies have emerged as critical components in the management of advanced PSCC. Recent developments in clinical research have revealed the effectiveness of new therapeutic strategies. By elucidating the mechanism of action and clinical evidence supporting these treatments, we strive to offer insights into optimizing treatment strategies and enhancing the quality of care for patients affected by this complex disease.

Efficacy and safety of antibody-drug conjugates in the treatment of urothelial cell carcinoma: a systematic review and meta-analysis of prospective clinical trials.

Introduction: Urothelial carcinoma (UC) is a refractory disease for which achieving satisfactory outcomes remains challenging with current surgical interventions. Antibody-drug conjugates (ADCs) are a novel class of targeted therapeutics that have demonstrated encouraging results for UC. Although there is a limited number of high-quality randomized control trials (RCTs) examining the use of ADCs in patients with UC, some prospective non-randomized studies of interventions (NRSIs) provide valuable insights and pertinent information. We aim to assess the efficacy and safety of ADCs in patients with UC, particularly those with locally advanced and metastatic diseases. Methods: A systematic search was conducted across PubMed, Embase, the Cochrane Library, and Web of Science databases to identify pertinent studies. Outcomes, such as the overall response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), adverse events (AEs), and treatment-related adverse events (TRAEs), were extracted for further analyses. Results: Twelve studies involving 1,311 patients were included in this meta-analysis. In terms of tumor responses, the pooled ORR and DCR were 40% and 74%, respectively. Regarding survival analysis, the pooled median PFS and OS were 5.66 months and 12.63 months, respectively. The pooled 6-month PFS and OS were 47% and 80%, while the pooled 1-year PFS and OS were 22% and 55%, respectively. The most common TRAEs of the ADCs were alopecia (all grades: 45%, grades ≥ III: 0%), decreased appetite (all grades: 34%, grades ≥ III: 3%), dysgeusia (all grades: 40%, grades ≥ III: 0%), fatigue (all grades: 39%, grades ≥ III: 5%), nausea (all grades: 45%, grades ≥ III: 2%), peripheral sensory neuropathy (all grades: 37%, grades ≥ III: 2%), and pruritus (all grades: 32%, grades ≥ III: 1%). Conclusion: The meta-analysis in this study demonstrates that ADCs have promising efficacies and safety for patients with advanced or metastatic UC. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier: CRD42023460232.