Differential expression of serum CXCL9 and CXCL10 levels in vitiligo patients and their correlation with disease severity and stability: A cross-sectional study.

Aulakh S ，Goel S ，Kaur L ，Gulati S ，Kaur M ，Chopra D ，Sarangal R ，Batra J ... -  《-》

Interferon-ε loss is elusive 9p21 link to immune-cold tumors, resistant to immune-checkpoint therapy and endogenous CXCL9/10 induction.

Copy-number (CN) loss of chromosome 9p, or parts thereof, impair immune response and confer ICT resistance by direct elimination of immune-regulatory genes on this arm, notably IFNγ genes at 9p24.1, and type-I interferon (IFN-I) genes at 9p21.3. We recently found that the primary 9p-loss human-tumor immune readout, however, is indirect (CXCL9/10 depletion at 4q21.1), and in mice, uncovered little-studied IFN-I interferon-ε (IFNϵ) deletion as the pivotal 9p21.3 link to TME immune-cell suppression. The central role of CXCL9 and/or CXCL10 in TME, has generated intense interest in cellular sources and regulation of these chemokines. We developed a focal gene-deletion strategy, termed MACHETE, to study the contribution of individual IFN-I genes to TME immune-cell populations in murine models. In this report, MACHETE-engineered deletions of Cdkn2a/b alone, MTAP vs Cdkn2a/b with progressively increasing numbers of IFN-I genes, ΔS and ΔL, at mouse chr4C4 syntenic to human chr9p21.3, were used to assess IFN-I contribution of to cxcl9 and cxcl10 expression levels. This research perspective updates and explicates the rapidly emerging body of clinical 9p CN alteration (CNA)/ICT data (13 reports, 36 cohorts, 3.5 years), and executes clinical and experimental 9p, IFNϵ and CXCL9/10 studies of this novel genomic ICT-resistance mechanism. We analyzed 9p, 9p21.3 and 9p24.1 influence on IFN-I gene-expression and using CIBERSORT, Kassandra, MCPcounter, xCell immune-cell deconvolution probed CD8 T-cells, dendritic cells (DCs), macrophages, neutrophils; subtypes, molecules, and sub-cluster mechanisms in HPV- HNSC (TCGA, n=343; CPTAC (n=105) and 32 cell lines, and pancreatic ductal adenocarcinoma (PDAC) (177 TCGA, 44 lines). We also include pan (34)-tumor analysis, focused on 4 highly aneuploid tumors-HPV- HNSC, NSCLC (non-squamous [NS) and squamous [LUSC]), and PDAC-and mouse-model PDAC and NS NSCLC studies. To identify CXCL9/10-CXCR3 axis sources and regulation, we analyzed 9p21.3, IFN-I deletion size and depth in human tumors and cell lines, and scRNA-sequencing of mouse models, for cell type, subtype and subcluster expression of CXCL9 and CXCL10. The latter metrics included numbers of Cxcl9/10+ immune cells, percentages of Cxcl9/10 -expressing cells, per-cell expression levels of each CXCL gene, and total cell Cxcl9 and cxcl10+ fractions.. In HPV- HNSC, IFNϵ was the most highly expressed IFN-I gene in the TME, the only IFN-I gene detectable in cell lines; suppressed (with IFNA1, IFNA13 and IFNK) in 9p21.3 (but not 9p24.1) loss tumors, adjusting for SCNA level, and in mediation analysis, IFNϵ loss was a statistically significant direct 9p21 link to effector-cell suppression (of CD8, T-cells, myeloid DCs and neutrophils), and was profoundly tissue specific. GSEA-pathway analysis of IFNϵ identified NFκB and inflammatory response as the top two IFNϵ-loss depleted pathways in TCGA and cell lines. 9p21.3 shallow and deep (and ΔS and ΔL) deletions were associated with progressive CXCL9/10-CXCR3 axis suppression in multiple multivariable models. Ifnϵ was the primary cell-intrinsic IFN-I signal to Cxcl9/10 in PDAC, confirmed in KPL-3M lung scRNA-seq data. In support of a causal link between IFNϵ and TME, CD8 T-cells and myeloid DCs, and CXCL9/10, this analysis revealed higher numbers of Cxcl9/10+ DCs, macrophages and neutrophils in IFN-intact ΔS (vs ΔL). We found higher percentages of CXCL9- and CXCL10-expressing DCs, macrophages and neutrophils in IFN-I WT ΔS (vs ΔL) tumors, and Cxcl9/10+ per-cell expression levels in macrophages (P=6.2e-4 for CXCL9: P=3.3e-6 for CXCL10). M1 was the main macrophages subtype driving the difference in CXCL9 between ΔS and ΔL tumors (P=2.1e-3), and CCL5+ in CXCL10 (P=0.018). DC subclustering revealed that both cDC1 and cDC2 produced CXCL9, while only cDC2 produced CXCL10, and the difference between ΔS and ΔL was mainly driven by cDC2. Although no difference was observed in overall per-cell expression level of each CXCL gene in ΔS vs ΔL tumors, total DC CXCL9+ and CXCL10+ fractions were higher in ΔL. We identify IFNϵ loss as the elusive 9p21 link to human immune-cold, CXCL9/10-CXCR3 axis-depleted tumors. Extending mouse-model studies of IFN-I on TME immune-cell levels, we found that IFNϵ loss is the primary cell-intrinsic 9p21 immune signal to DC and macrophage subtype and subcluster expression of CXCL9 and CXCL10, the major sources of these chemokines. Larger deletions to 9p24 further restrict CXCL9/10 induction via loss of IFN-γ-pathway gene, JAK2. 9p-loss tumors with these distinct IFN defects operative in the TME, lack the capacity of endogenous CXCL9/10 induction in an immune-desert, ICT-resistant state. These data, the extensive 9p loss/ICT resistance body of evidence, and early NSCLC DC-chemokine vaccine trials, have led to a DC vaccine engineered with a CXCL9/10 payload, designed to bypass the specific, severe chemokine deficit in 9p loss tumors.

Zhao X ，Liu B ，William WN ，Tsanov KM ，Ho YJ ，Barriga FM ，Lim RJ ，Trifas M ，Du Y ，Lowe SW ，Dubinett SM ，Davoli T ，Lippman SM ... -  《-》

Role of chemokines CXCL9, CXCL10, CXCL11, and CXCR3 in the serum and minor salivary gland tissues of patients with Sjögren's syndrome.

This study aimed to investigate the serum and expression levels of C-X-C motif chemokine ligand 9 (CXCL9), CXCL10, CXCL11, and CXC receptor 3 (CXCR3) in minor salivary glands (MSGs) of patients with primary Sjögren's syndrome (pSS), and to explore their correlations with clinical parameters. Serum samples from 49 patients diagnosed with pSS, 33 patients with rheumatoid arthritis (RA), and 30 healthy controls (HCs) were collected for measurements of CXCL9, CXCL10, CXCL11, and CXCR3. Additionally, CXCL levels in the MSG tissues were measured in 41 patients who underwent MSG biopsy. Correlations between CXCL and CXCL/CXCR levels in serum/MSG tissues and clinical factors/salivary scintigraphy parameters were analyzed. Serum CXCL11 and CXCR3 showed statistically significant differences among patients with pSS and RA and HCs (serum CXCL11, pSS:RA:HC = 235.6 ± 500.1 pg/mL:90.0 ± 200.3 pg/mL:45.9 ± 53.6 pg/mL; p = 0.041, serum CXCR3, pSS:RA:HC = 3.27 ± 1.32 ng/mL:3.29 ± 1.17 ng/mL:2.00 ± 1.12 ng/mL; p < 0.001). Serum CXCL10 showed a statistically significant difference between pSS (64.5 ± 54.2 pg/mL) and HCs (18.6 ± 18.1 pg/mL, p < 0.001), while serum CXCL9 did not exhibit a significant difference among the groups. Correlation analysis of clinical factors revealed that serum CXCL10 and CXCL11 levels positively correlated with erythrocyte sedimentation rate (r = 0.524, p < 0.001 and r = 0.707, p < 0.001, respectively), total protein (r = 0.375, p = 0.008 and r = 0.535, p < 0.001, respectively), globulin (r = 0.539, p < 0.001 and r = 0.639, p < 0.001, respectively), and European Alliance of Associations for Rheumatology SS Disease Activity Index (r = 0.305, p = 0.033 and r = 0.321, p = 0.025). Additionally, serum CXCL10 negatively correlated with the Schirmer test score (r = - 0.354, p = 0.05), while serum CXCL11 positively correlated with the biopsy focus score (r = 0.612, p = 0.02). In the MSG tissue, the percentage of infiltrating CXCL9-positive cells was highest (75.5%), followed by CXCL10 (29.1%) and CXCL11 (27.9%). In the correlation analysis, CXCL11-expressing cells were inversely related to the mean washout percentage on salivary gland scintigraphy (r =  - 0.448, p = 0.007). Our study highlights distinct serum and tissue chemokine patterns in pSS, emphasizing CXCL9's potential for early diagnosis. This suggests that CXCL10 and CXCL11 are indicators of disease progression, warranting further investigation into their roles in autoimmune disorders beyond pSS.

Kim JW ，Ahn MH ，Jung JY ，Suh CH ，Han JH ，Kim HA ... -  《-》

Role of miR-16, 146a, 19b and 720 gene expressions in the pathogenesis and diagnosis of vitiligo.

Vitiligo is a common long-term depigmenting skin disorder that is characterized by patches of skin losing their pigment. To evaluate serum/tissue levels of miR-16, 146a, 19b and 720 in vitiligo patients and healthy controls, also analyzing the correlations between all biomarkers to indicate whether those can be used to early diagnose vitiligo patients. Forty-subjects were included, divided into two equal groups, 20 healthy matched individuals and 20 vitiligo patients. For all groups a 5 mL venous blood sample for serum isolation was taken and analyzed for the serum level of miRNAs. For tissue analysis, 3 mm biopsy was taken. For all patients Vitiligo area scoring index (VASI), vitiligo disease activity (VIDA), disease duration and extent percentages were calculated. No significant difference was observed in age and sex ratio among the two groups (p > 0.05). Serum, expression levels for miR-16, 146a, and 19b were overexpressed in vitiligo patients as compared to healthy controls with p-value 0.000 for all biomarkers. While miR-720 was reported low in vitiligo patients compared to controls (p = 0.000). For tissue samples, miR-16, 146a, 19b were overexpressed in vitiligo patients with p-values 0.000, 0.000 and < 0.001 respectively, while for the expression level of miR-720 in tissue, the level was low compared to controls (p = 0.000). There are positive correlations between VASI and miR-16, 146a in serum and miR-146a in tissue. Also positive correlations between disease extent and both miR-16 and miR-146a in serum and in tissue was found. A negative correlation between VIDA and miR-720 in serum was found. Various correlations between the selected miRNAs were reported. Based upon the expression levels of miR-16, 146a, 19b and 720 in both serum and tissue, these biomarkers can be used as early indicators for vitiligo.

Shaker OG ，Abd Elrahim TA ，Azzam S ，El-Zook MM ，Aboraia NM ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》