Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) has demonstrated remarkable therapeutic effects in ALK-positive non-small cell lung cancer (NSCLC) patients. Identifying prognostic biomarkers can enhance the clinical efficacy of relapsed or refractory patients.
We profiled 737 plasma proteins from 159 pre-treatment and on-treatment plasma samples of 63 ALK-positive NSCLC patients using data-independent acquisition-mass spectrometry (DIA-MS). The consensus clustering algorithm was used to identify subtypes with distinct biological features. A plasma-based prognostic model was constructed using the LASSO-Cox method. We performed the Mfuzz analysis to classify the patterns of longitudinal changes in plasma proteins during treatment. 52 baseline plasma samples from another independent ALK-TKI treatment cohort were collected to validate the potential prognostic markers using ELISA.
We identified three subtypes of ALK-positive NSCLC with distinct biological features and clinical efficacy. Patients in subgroup 1 exhibited activated humoral immunity and inflammatory responses, increased expression of positive acute-phase response proteins, and the worst prognosis. Then we constructed and verified a prognostic model that predicts the efficacy of ALK-TKI therapy using the expression levels of five plasma proteins (SERPINA4, ATRN, APOA4, TF, and MYOC) at baseline. Next, we explored the longitudinal changes in plasma protein expression during treatment and identified four distinct change patterns (Clusters 1-4). The longitudinal changes of acute-phase proteins during treatment can reflect the treatment status and tumor progression of patients. Finally, we validated the prognostic efficacy of baseline plasma CRP, SAA1, AHSG, SERPINA4, and TF in another independent NSCLC cohort undergoing ALK-TKI treatment.
This study contributes to the search for prognostic and drug-resistance biomarkers in plasma samples for ALK-TKI therapy and provides new insights into the mechanism of drug resistance and the selection of follow-up treatment.

BACKGROUND: Vulvar lichen sclerosus (VLS) in girls presents with itching, dysuria, and constipation and may result in the loss of vulvar architecture. In patients with an ambiguous clinical presentation, reflectance confocal microscopy (RCM) could be a helpful noninvasive diagnostic tool. The aim of this study was to describe the RCM characteristics of VLS and explore the clinical application value of RCM in therapeutic monitoring.
METHODS: Sixteen patients with VLS were included in the study. All patients were periodically evaluated clinically with RCM, and different treatment regimens were given based on the patient\'s clinical appearances and RCM features.
RESULTS: Some major key diagnostic features of VLS can be observed by RCM, including round to oval cyst-like structures with medium-to-low-refractive keratinoid substances (75%), thinning of the epidermal thickness (100%), destruction of the ring-like structures around dermal papillae (100%), disorderly distributed coarse medium-refractive fibrous material (100%),polygonal, plump, high-refractive cellular structures and linear low-refractive canalicular structures (100%). All of these characteristics had a high correspondence with histopathological features. The clinical manifestations improved after individualized treatment regimens based on the clinical appearances and RCM features.
CONCLUSIONS: RCM allows the visualization of major key diagnostic features of VLS and represents a valid option for objective therapeutic monitoring.

Rapid screening and early treatment of lung infection are essential for effective control of many epidemics such as Coronavirus Disease 2019 (COVID-19). Recent studies have demonstrated the potential correlation between lung infection and the change of back skin temperature distribution. Based on these findings, we propose to use low-cost, portable and rapid thermal imaging in combination with image-processing algorithms and machine learning analysis for non-invasive and safe detection of pneumonia. The proposed method was tested in 69 subjects (30 normal adults, 11 cases of fever without pneumonia, 19 cases of general pneumonia and 9 cases of COVID-19) where both RGB and thermal images were acquired from the back of each subject. The acquired images were processed automatically in order to extract multiple location and shape features that distinguish normal subjects from pneumonia patients at a high accuracy of 93 % . Furthermore, daily assessment of two pneumonia patients by the proposed method accurately predicted the clinical outcomes, coincident with those of laboratory tests. Our pilot study demonstrated the technical feasibility of portable and intelligent thermal imaging for screening and therapeutic assessment of pneumonia. The method can be potentially implemented in under-resourced regions for more effective control of respiratory epidemics.

Chimeric antigen receptor T cell (CAR-T) therapy is a new and effective form of adoptive cell therapy that is rapidly entering the mainstream for the treatment of CD19-positive hematological cancers because of its impressive effect and durable responses. Huge challenges remain in achieving similar success in patients with solid tumors. The current methods of monitoring CAR-T, including morphological imaging (CT and MRI), blood tests, and biopsy, have limitations to assess whether CAR-T cells are homing to tumor sites and infiltrating into tumor bed, or to assess the survival, proliferation, and persistence of CAR-T cells in solid tumors associated with an immunosuppressive microenvironment. Radionuclide-based molecular imaging affords improved CAR-T cellular visualization and therapeutic monitoring through either a direct cellular radiolabeling approach or a reporter gene imaging strategy, and endogenous cell imaging is beneficial to reflect functional information and immune status of T cells. Focusing on the dynamic monitoring and precise assessment of CAR-T therapy, this review summarizes the current applications of radionuclide-based noninvasive imaging in CAR-T cells visualization and monitoring and presents current challenges and strategic choices.

Malignant osteolysis associated with irreversible primary bone tumors and bone metastases remains a clinically urgent problem. Exploiting the imaging and therapy function of flexible nanomedicine can provide an alternative for therapeutic navigation and monitoring of malignant osteolysis. Here, we report the development of albumin-based gadolinium oxide nanoparticles loaded with doxorubicin and conjugated with bone-seeking alendronate for targeted delivery and therapeutic monitoring. Compared with nontargeted nanomedicine, bone-seeking accumulation and retention can be proven by MRI in a rat model of focal malignant osteolysis. Meanwhile, we observed a whole-body distribution in the consecutive SPECT imaging after radiolabeling with 125I, SPECT imaging also indicated the enhanced bone tumor accumulation and prolonged retention. Resulting from the high drug loading and 131I labeling efficiency, the targeted nanomedicine exhibited significant chemotherapy and inter-radiotherapy capacity. Ultimately, the tumor burden of rats was obviously decreased except for the nontargeted group and the empty carrier group. In vivo CT imaging and pathological analysis revealed that the combined therapy was an efficient measure for antiosteolysis. Our findings suggest that albumin-based nanomedicine can provide a platform for bone-seeking diagnosis and therapeutic monitoring.

The utility of serum progastrin-releasing peptide (ProGRP) and neuron-specific enolase (NSE) as biomarkers for treatment monitoring and as prognostic factors was investigated in small cell lung cancer (SCLC) patients. Patients were first diagnosed pathologically at the First Affiliated Hospital of the University of Science and Technology of China and had their serum ProGRP and NSE levels measured using an electrochemiluminescence immunoassay. A total of 120 SCLC patients were enrolled. In responsive patients, ProGRP levels decreased significantly following two cycles of chemotherapy and continued to decline over the course of treatment. However, this decrease in ProGRP levels was not observed in non-responsive patients. Changes in ProGRP levels were more accurate than changes in NSE levels for monitoring the effects of chemotherapy in patients with SCLC. Following two treatment cycles or after the occurrence of drug resistance, changes in ProGRP levels in patients with low ProGRP levels at the time of diagnosis were not notably, regardless of whether or not patients were responders. The area under the receiver operating characteristic curve of the decline in ProGRP levels as a therapeutic biomarker of SCLC was 0.9643, and the cut-off value was 55.02%. A decline in ProGRP levels maybe a good predictor of objective response to chemotherapy in patients with SCLC with higher ProGRP levels at diagnosis. This model is expected to replace or be combined with imaging to predict chemotherapeutic treatment effects in patients with SCLC.

We aimed to compare the diagnostic efficiency of proGRP and NSE on SCLC and to investigate whether the change of proGRP level would predict therapeutic response. Patients who were firstly diagnosed pathologically in Nanjing Chest Hospital and measured proGRP level consecutively were enrolled in the study. ProGRP level was detected using Elecsys ProGRP Assay. Totally 75 SCLC, 234 NSCLC and 264 benign lung diseases (BLD) were enrolled. Both proGRP and NSE levels in SCLC were significantly higher than those in NSCLC and BLD, and proGRP in extensive stage SCLC was higher than which in limited stage (P ≤ .001). The diagnostic efficiency of proGRP on SCLC was higher than that of NSE, but when the two biomarkers were bind together, the diagnostic efficiency was the best. When SCLC was differentiated from NSCLC and BLD, the cut-off values were 114.35 pg/mL and 162.55 pg/mL respectively. For treatment responsive patients, proGRP level decreased markedly after the first cycle of therapy and kept a continued momentum of decline during treatment. But for unresponsive patients, no obvious decline was observed. ProGRP had higher diagnostic efficiency on SCLC when compared to NSE, and it could better predict therapeutic response of pulmonary target lesions on chemotherapy.

This work reports a graphene oxide-based nanovehicle with conjugation of pegylated folate for targeted delivery of anticancer drugs and fluorescein-labeled peptide for therapeutic self-monitoring in vitro and in vivo. The nanovehicle could absorb hydrophobic and aromatic drug molecules with high loading capacity and efficiency of more than 1.7 mg mg(-1) and 90%, respectively. MTT and flow cytometric assays demonstrated that the drug-loaded nanovehicle could specifically transport and release the drugs into the folate receptor high-expressed cancer cells, which ensured a high therapeutic efficiency to cancer cells and prevented the injury to normal cells. Moreover, confocal fluorescence imaging confirmed that the drug-induced cancer cell death could be visualized with the light-up fluorescence of fluorescein activated by caspase-3. The targeted delivery of drug and self-evaluation of therapeutic efficacy were further successfully realized by living imaging in tumor-bearing mice, which broaden the applications of this theranostic system in vivo and may offer new opportunities for precise cancer treatment.

Simultaneous targeted cancer imaging, therapy and real-time therapeutic monitoring can prevent over- or undertreatment. This work describes the design of a multifunctional nanomicelle for recognition and precise near-infrared (NIR) cancer therapy. The nanomicelle encapsulates a new pH-activatable fluorescent probe and a robust NIR photosensitizer, R16FP, and is functionalized with a newly screened cancer-specific aptamer for targeting viable cancer cells. The fluorescent probe can light up the lysosomes for real-time imaging. Upon NIR irradiation, R16FP-mediated generation of reactive oxygen species causes lysosomal destruction and subsequently trigger lysosomal cell death. Meanwhile the fluorescent probe can reflect the cellular status and in situ visualize the treatment process. This protocol can provide molecular information for precise therapy and therapeutic monitoring.