Enzo Lalli

Background/Objectives: CD19-directed chimeric antigen receptor (CAR) T-cell therapy has transformed the treatment of relapsed/refractory large B-cell lymphoma (r/r LBCL), yet primary resistance and relapse remain common. We evaluated how recent clinical and translational evidence refines established resistance frameworks and which knowledge gaps prevent the relative contribution of individual mechanisms from being determined. Methods: We conducted a structured narrative review of 14 selected clinical and translational studies addressing tumor-, product-, host-, and microenvironment-related dimensions of treatment failure, synthesized across four interpretive domains and compared with nine previous reviews. Results: Durable benefit was associated with favorable tumor and immune transcriptional programs and greater CAR T-cell fitness, expansion, or persistence. Treatment failure was associated with tumor-intrinsic resistance programs, exhausted T-cell states, systemic inflammatory signals, and suppressive tumor-microenvironment features, including PD-L1-expressing macrophages. Antigen escape remained relevant, but incomplete serial CD19 assessment precluded conclusions about its relative contribution. Comparison with earlier reviews showed continuity rather than replacement, with LBCL-focused evidence adding biological resolution. Conclusions: Resistance and relapse after CD19 CAR T-cell therapy in LBCL are multifactorial. Prospective longitudinal studies integrating tumor tissue, apheresis and manufactured products, peripheral blood, and matched relapse samples are needed to validate predictive biomarkers and guide rational treatment strategies.

Background/Objectives: Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy with axicabtagene ciloleucel (axi-cel) improves outcomes in relapsed/refractory large B-cell lymphoma (LBCL), but many patients relapse despite retained CD19 expression. We explored baseline tumor transcriptional features associated with event-free survival (EFS) after axi-cel. Methods: We reanalyzed baseline NanoString IO 360 profiles from the randomized ZUMA-7 trial (axi-cel, n = 134; standard of care [SOC], n = 122) using differential expression, gene set enrichment, MCP-counter deconvolution, Kaplan–Meier and Cox models adjusted for tumor burden and cell of origin, and gene-by-treatment interaction models. Results: T-cell exhaustion and HLA transcripts were not associated with response in either arm, and no transcript passed FDR correction in differential expression. In the axi-cel arm, 13 of 14 modeled transcripts remained associated with EFS after adjustment; eight (MS4A1, CD19, TNFRSF17, HLA-DOB, CD45RA, DUSP5, KLRD1 and WNT11) were FDR-supported at every survival-analysis stage within the 25 prioritized candidates, but not panel-wide. Consistent with the primary ZUMA-7 report, higher B-cell transcript expression was associated with longer EFS. Interaction testing gave borderline support for a differential association between arms only for KLRD1 and DUSP5 (FDR = 0.049), robust to arm-stratified models; other candidates showed no or only nominal specificity. Apart from the B-lineage score (FDR = 0.029), no estimated immune or stromal population was associated with response. Conclusions: Baseline B-cell transcriptional programs and a small set of gene-level candidates are associated with EFS after axi-cel in ZUMA-7. These exploratory findings do not establish predictive value and require independent validation.

Background/Objectives: Adrenocortical carcinoma (ACC) is a rare malignancy in which overexpression of steroidogenic factor-1 (SF-1/NR5A1) and aberrant activation of canonical Wnt/β-catenin signaling are important oncogenic events. However, the extent to which these regulatory axes converge or interact at the transcriptional level remains unclear. We investigated their relationship using bulk transcriptomic and regulatory-network approaches. Methods: Regulatory network inference using RTN/ARACNe was applied to the TCGA-ACC cohort. NR5A1 and β-catenin-associated TCF/LEF regulon activities were evaluated in perturbation datasets and tested for associations with CpG island methylator phenotype (CIMP), overall survival, and gene-level interaction effects. Candidate modulators of NR5A1 activity were assessed using the MINDy algorithm. The effects of cBAF inhibition on NR5A1 regulon activity were also evaluated in H295R and CU-ACC1 cells. Results: NR5A1 knockdown repressed steroidogenic pathways, whereas β-catenin knockdown predominantly suppressed Wnt/β-catenin signaling. In TCGA-ACC, NR5A1 regulon activity was associated with CIMP-high status and overall survival. In contrast, β-catenin-related regulons were not significantly associated with CIMP-high status after adjustment for NR5A1 activity, and no significant multiplicative interaction effects were identified. Fewer than 3% of protein-coding genes showed improved fit in models including NR5A1 × TCF/LEF interaction terms, without enrichment for steroidogenic or Wnt/β-catenin-related pathways. CTNNB1 was identified as a statistically significant but low-ranking positive modulator of NR5A1 activity, whereas CTNNBIP1 was a top-decile negative modulator. cBAF inhibition was associated with NR5A1 regulon repression in both cell models. Conclusions: These findings indicate limited detectable global transcriptional convergence between NR5A1 and canonical β-catenin-related regulons in the evaluated bulk transcriptomic frameworks. Potential relationships between these pathways may depend on more localized, chromatin-dependent, protein-level, or context-specific regulatory mechanisms. NR5A1 regulon activity showed more consistent associations with CIMP-high status and clinical outcome than the β-catenin/TCF-LEF regulons in the evaluated TCGA-ACC models. The modulation patterns associated with CTNNB1 and CTNNBIP1, together with the repression of NR5A1 regulon activity following cBAF inhibition, raise the possibility that NR5A1 acts as a context-dependent regulatory node connecting oncogenic signaling and chromatin-remodeling mechanisms in ACC. These findings support further investigation into the role of chromatin-remodeling complexes in sustaining NR5A1-driven transcriptional programs in ACC.

DAX-1 (NR0B1) is a pivotal regulator of mammalian reproductive and endocrine development. Discovered as a gene whose dosage imbalance can reverse sex in XY individuals, DAX-1 is now recognized as a key component of the network controlling gonadal formation and function. Despite decades of research, the molecular mechanisms of its function in gonad development and function remain only partially understood. We combine genetic, developmental, molecular and biochemical perspectives to present how DAX-1 regulates gene expression from early sex determination and gonadal differentiation to the maintenance of steroidogenic homeostasis in adrenal and gonadal tissues. Recent advances have reshaped our view of DAX-1 beyond its classical role as a transcriptional repressor. Evidence shows that it functions within dynamic transcriptional networks, interacting with regulators such as SF-1 (NR5A1), SOX9 and other nuclear receptors to fine-tune gene expression in a context-dependent manner. Genomic, structural, and proteomic studies reveal that DAX-1 participates in complexes integrating developmental and hormonal cues, coordinating differentiation and steroidogenesis. Moreover, its emerging roles in RNA-associated gene regulation broaden its functions beyond canonical nuclear receptor signaling. We revisit DAX-1 contribution to sex determination and differentiation from an evolutionary and mechanistic viewpoint, emphasizing its interactions with the SRY–SOX9 axis and its dosage-sensitive influence on gonadal fate. The developmental and clinical consequences of DAX-1 mutations and copy number variations manifest as a spectrum of human phenotypes, from adrenal hypoplasia congenita to differences/disorders of sex development (DSD), highlighting its essential role in maintaining endocrine balance.

Background: Adrenocortical carcinoma (ACC) is a rare, aggressive malignancy where endogenous steroid excess may foster immune evasion. However, whether this hormonal axis directly modulates the antigen presentation machinery remains unclear. Methods: We applied an immunoinformatics approach to the TCGA-ACC cohort (n = 79) to investigate relationships among steroid phenotype, HLA expression, tumor microenvironment (TME), and patient outcome. Key findings were assessed in an independent validation cohort (ENSAT-ACC, n = 44) using C1A/C1B molecular subtypes corresponding to the steroid phenotypes. Results: Stratification by steroid phenotype revealed two distinct immunological profiles. The high steroid production (HSP) phenotype was associated with suppressed HLA expression and a lymphocyte-depleted “cold” TME. In contrast, the low steroid production (LSP) phenotype displayed elevated HLA expression, enriched T-cell infiltration, and upregulation of immune checkpoints (e.g., PDCD1, CTLA4), consistent with an inflamed but exhausted TME. The core signature of HLA downregulation in the HSP-like phenotype (C1A) and the significant survival advantage of the LSP-like phenotype (C1B) were confirmed in the validation cohort, demonstrating biological robustness despite platform and sample size differences. Conclusions: These findings identify the steroid phenotype as a critical regulator of immune escape in ACC. Our results support incorporating this stratification as a biomarker for patient selection, identifying LSP tumors as the subgroup most likely to benefit from immune checkpoint blockade due to their “hot” yet exhausted microenvironment.

Objective: Gene dosage is at the core of the biological activity of the steroidogenic factor-1 (SF-1/NR5A1) transcription factor. Its overexpression in adrenocortical carcinoma (ACC) is associated with enhanced proliferation and invasive capacities, steroid modulation, immune suppression, and poor prognosis. Surprisingly, 3 independent studies showed less than 10% agreement in identifying SF-1–regulated genes in the same ACC cell line, raising concerns about technical reproducibility and methodological consistency. This study aimed to reconcile discrepancies in SF-1–regulated gene identification across independent studies using a systematic approach. Design and Methods: We reanalysed datasets from those studies using an in silico SF-1 regulon obtained from ACC TCGA data as an external reference to evaluate transcriptional patterns. Additionally, we assessed how threshold selection impacts the overlap between experiments and optimized this process. Furthermore, we performed functional experiments to evaluate how variations in SF-1 dosage impact target gene expression. Results: Our analysis revealed comparable transcriptional patterns across all studies, reconciling transcriptional signatures and phenotypes. Threshold optimization identified consensus sets of genes responsive to SF-1 perturbations. Functional experiments confirmed that variations in SF-1 dosage significantly impact gene expression, explaining discrepancies in previous studies, and evidenced negative autoregulation of the SF-1 transcript by its encoded protein both in ACC cells and in a mouse model of Sf-1 overexpression in the adrenal cortex. Conclusions: Our findings deepen our understanding of SF-1 regulatory activity in ACC and demonstrate that dosage is critical for observed gene expression patterns. Our integrative approach improves reproducibility and biological interpretation, offering a framework to reconcile cross-study findings.

AlphaMissense is a valuable resource for discerning important functional regions within proteins, providing pathogenicity heatmaps that highlight the pathogenic risk of specific mutations along the protein sequence. However, due to protein folding and long-range interactions, the actual structural alterations with functional implications may be occurring at a distance from the mutation site. As a result, the identification of the most sensitive structural regions for protein function may be hampered by the presence of mutations that indirectly affect the critical regions from a distance. In this study, we illustrate how the use of AlphaMissense predictions to train an XGBoost regression model on structural features extracted from the structures of protein variants predicted by OmegaFold enables the definition of a new explainability metric: a residue-based importance score that highlights the most critical structural domains within a protein sequence. To verify the accuracy of our approach, we applied it to the extensively studied protein DAX-1 and successfully identified critical structural domains. Notably, as this score only requires knowledge of the protein’s amino acid sequence, it is valuable in guiding experimental investigations aimed at discovering functionally crucial regions in proteins that have been poorly characterized.

Escape from immune destruction is widely recognized as one hallmark of cancer. Immune checkpoint inhibitors, targeted at counteracting suppressive mechanisms that impair elimination of cancer cells by the immune system, have revolutionized the therapy of many types of cancer. An essential condition for efficient destruction of cancer cells is that solid tumors are infiltrated with immune cells able to eliminate them. Adrenocortical carcinomas (ACCs) as a group are among the immunologically “coldest” (immune cell-depleted) tumors. Several mechanisms may acccount for this finding: immunosuppressive effects of glucocorticoids produced by the tumor, activation of the Wnt/β-catenin signaling pathway causing immune exclusion, and presence of TP53 mutations associated with reduced chemokine secretion and natural killer cell activity. This may explain the overall limited success obtained up to the present time by the use of immunotherapy in the treatment of patients with ACCs at an advanced stage ( 1). Nevertheless, not all ACCs are created equal: total leukocyte infiltration as well as the abundance of lymphocyte subsets in the tumor microenvironment greatly differs in the ACC subtype characterized by high steroid hormone production compared to tumors producing little or no steroids ( 2). Several studies have shown that immune parameters have a prognostic value in both children and adult ACC ( 3, 4), indicating that the immune response has indeed an important role in fighting against ACC growth and spread. However, a precise estimate of the expression of immune checkpoint molecules in ACC is needed to assess the probability of success of immunotherapy. The study by Landwehr et al ( 5) fills this knowledge gap since it reports data about the expression of PD-1, PD-L1, and CTLA-4 in a large series (considered the rarity of this tumor type) of ACC and their correlation with clinical parameters and prognosis. The authors have shown that PD-1 and its ligand PD-L1 were expressed in slightly less than 30% of cases, while CTLA-4 was expressed in more than 50% of samples. PD-1 expression was correlated with longer progression-free survival and with the number of tumor-infiltrating T cells. As the authors observed, in ACC, PD-1 expression may be a proxy for tumor-infiltrating cytotoxic CD8⁺ T cells targeting cancer antigens by high-afffinity T-cell receptors. These results are consistent with studies in other cancer types (colorectal carcinoma, non–small cell lung cancer), where PD-1 expression is significantly correlated with a better clinical outcome, while in breast cancer it is associated with a worse prognosis. Those contrasting data may be related to different degrees of T-cell activation in those tumors. It is interesting to remark that in the study by Landwehr et al, no prognostic correlation was observed for PD-L1 expression, while a previous study performed in The Cancer Genome Atlas adrenocortical carcinoma cohort found high expression of this marker associated with longer postoperative survival ( 6). Methodological issues [study of protein expression by immunohistochemistry in ( 5), mRNA analysis in ( 6)] and different cutoffs used may, at least in part, account for those discrepancies. Overall, the study by Landwehr et al is encouraging about the possibility of relieving T-cell inhibition by immunotherapy in a fairly high percentage of cases of ACC, after selection for PD-1 (and possibly CTLA-4) expression, in association with microsatellite instability screening, a more frequent finding in ACC than previously recognized ( 7). Since immunotherapy is reserved to patients in advanced stages who have often been heavily treated, one open question remains if and how previous therapies can modify the expression of checkpoint inhibitor molecules. The present study could not address this important point because most patients studied had localized tumors that did not require systemic treatment.