Many patient-derived tumor models have emerged recently. However, their potential to guide personalized drug selection remains unclear. Here, we report patient-derived tumor-like cell clusters (PTCs) for non-small cell lung cancer (NSCLC), capable of conducting 100-5,000 drug tests within 10 days. We have established 283 PTC models with an 81% success rate. PTCs contain primary tumor epithelium self-assembled with endogenous stromal and immune cells and show a high degree of similarity to the original tumors in phenotypic and genotypic features. Utilizing standardized culture and drug-response assessment protocols, PTC drug-testing assays reveal 89% overall consistency in prospectively predicting clinical outcomes, with 98.1% accuracy distinguishing complete/partial response from progressive disease. Notably, PTCs enable accurate prediction of clinical outcomes for patients undergoing anti-PD1 therapy by combining cell viability and IFN-γ value assessments. These findings suggest that PTCs could serve as a valuable preclinical model for personalized medicine and basic research in NSCLC.

As new mutations continue to emerge, the ability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus to evade the human immune system and neutralizing antibodies remains a huge challenge for vaccine development and antibody research. The majority of neutralizing antibodies have reduced or lost activity against SARS-CoV-2 variants. In this study, we reported a novel protein surface display system on a mammalian cell for obtaining a higher-affinity antibody in high-throughput manner. Using a saturation mutagenesis strategy through integrating microarray-based oligonucleotide synthesis and single-cell screening assay, we generated a group of new antibodies against diverse prevalent SARS-CoV-2 variants through high-throughput screening the human antibody REGN10987 within 2 weeks. The affinity of those optimized antibodies to seven prevalent mutants was greatly improved, and the EC50 values were no higher than 5 ng/mL. These results demonstrate the robustness of our screening system in the rapid generation of an antibody with higher affinity against a new SARS-CoV-2 variant, and provides a potential application to other protein molecular interactions.

The recent global pandemic was a spillover from the SARS-CoV-2 virus. Viral entry involves the receptor binding domain (RBD) of the viral spike protein interacting with the protease domain (PD) of the cellular receptor, ACE2. We hereby present a comprehensive mutational landscape of the effects of ACE2-PD point mutations on RBD-ACE2 binding using a saturation mutagenesis approach based on microarray-based oligo synthesis and a single-cell screening assay. We observed that changes in glycosylation sites and directly interacting sites of ACE2-PD significantly influenced ACE2-RBD binding. We further engineered an ACE2 decoy receptor with critical point mutations, D30I, L79W, T92N, N322V, and K475F, named C4-1. C4-1 shows a 200-fold increase in neutralization for the SARS-CoV-2 D614G pseudotyped virus compared to wild-type soluble ACE2 and a sevenfold increase in binding affinity to wild-type spike compared to the C-terminal Ig-Fc fused wild-type soluble ACE2. Moreover, C4-1 efficiently neutralized prevalent variants, especially the omicron variant (EC50 = 16 ng/mL), and rescued monoclonal antibodies, vaccine, and convalescent sera neutralization from viral immune-escaping. We hope to next investigate translating the therapeutic potential of C4-1 for the treatment of SARS-CoV-2.

CRISPR/Cas12a (formerly Cpf1), an RNA-guided endonuclease of the Class II Type V-A CRISPR system, provides a promising tool for genome engineering. Over 10 Cas12a orthologues have been identified and employed for gene editing in human cells. However, the functional diversity among emerging Cas12a orthologues remains poorly explored. Here, we report a high-throughput comparative profiling of editing activities across 16 Cas12a orthologues in human cells by constructing genome-integrated, self-cleaving, paired crRNA–target libraries containing >40,000 guide RNAs. Three Cas12a candidates exhibited promising potential owing to their compact structures and editing efficiency comparable with those of AsCas12a and LbCas12a, which are well characterized. We generated three arginine substitution variants (3Rv) via structure-guided protein engineering: BsCas12a-3Rv (K155R/N512R/K518R), PrCas12a-3Rv (E162R/N519R/K525R), and Mb3Cas12a-3Rv (D180R/N581R/K587R). All three Cas12a variants showed enhanced editing activities and expanded targeting ranges (NTTV, NTCV, and TRTV) compared with the wild-type Cas12a effectors. The base preference analysis among the three Cas12a variants revealed that PrCas12a-3Rv shows the highest activity at target sites with canonical PAM TTTV and non-canonical PAM TTCV, while Mb3Cas12a-3Rv exhibits recognition features distinct from the others by accommodating for more nucleotide A at position −3 for PAM TATV and at position −4 for PAM ATCV. Thus, the expanded Cas12a toolbox and an improved understanding of Cas12a activities should facilitate their use in genome engineering.

Background: CRISPR-cpf1 is a single RNA-guided endonuclease system, becoming a promising tool in both prokaryotic and eukaryotic genome engineering. The editing efficiency of Cpf1 based engineering still requires improvements. However, limited information regarding the relationship between guide RNA sequence and on-target activity is available. To address these challenges, we developed a screening platform based on the association of Acidaminococcus sp. Cpf1(AsCpf1) DNA cleavage with cellular lethality. Major results: In total, we measured the activities of 12,544 guide RNAs, and observed a substantial variation of the editing efficiency depending on the design of the sequence. Based on this large-scale dataset, we designed and implemented a comprehensive computational model to predict activities of guide RNAs. Through comparison using simulated and experimental data, our approach outperformed existing algorithms, enabling selection of efficient guide RNAs. Conclusions: We refine on-target design rules and isolate the important sequence features that contribute to DNA cleavage, that is, AH dimers at position1-8 of protospacer promoting Cas12a activity while TK, GB dimer playing an inhibitory role. We validate guide RNA affinities designed by our optimized rules in both E.coli and 293T cells.

Homologous recombination (HR) is often used to achieve targeted gene integration because of its higher precision and operability compared with microhomology-mediated end-joining (MMEJ) or non-homologous end-joining (NHEJ). It appears to be inefficient for gene integration in animal cells and embryos due to occurring only during cell division. Here we developed genome-wide high-throughput screening and a subsequently paired crRNA library screening to search for genes suppressing homology-directed repair (HDR). We found that, in the reporter system, HDR cells with knockdown of SHROOM1 were enriched as much as 4.7-fold than those with control. Down regulating SHROOM1 significantly promoted gene integration in human and mouse cells after cleavage by clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein-9 nuclease (Cas9), regardless of the donor types. The knock-in efficiency of mouse embryos could also be doubled by the application of SHROOM1 siRNA during micro-injection. The increased HDR efficiency of SHROOM1 deletion in HEK293T cells could be counteracted by YU238259, an HDR inhibitor, but not by an NHEJ inhibitor. These results indicated that SHROOM1 was an HDR-suppressed gene and that the SHROOM1 knockdown strategy may be useful for a variety of applications, including gene editing to generate cell lines and animal models for studying gene function and human diseases.

Background CRISPR/Cas9 systems have been repurposed as canonical genome editing tools in a variety of species, but no application for the model strain Rhodobacter sphaeroides 2.4.1 was unveiled. Results Here we showed two kinds of programmable base editing systems, cytosine base editors (CBEs) and adenine base editors (ABEs), generated by fusing endonuclease Cas9 variant to cytosine deaminase PmCDA1 or heterodimer adenine deaminase TadA–TadA*, respectively. Using CBEs, we were able to obtain C-to-T mutation of single and double targets following the first induction step, with the efficiency of up to 97% and 43%; while the second induction step was needed in the case of triple target, with the screening rate of 47%. Using ABEs, we were only able to gain A-to-G mutation of single target after the second induction step, with the screening rate of 30%. Additionally, we performed a knockout analysis to identify the genes responsible for coenzyme Q10 biosynthesis and found that ubiF , ubiA , ubiG , and ubiX to be the most crucial ones. Conclusions Together, CBEs and ABEs serve as alternative methods for genetic manipulation in Rhodobacter sphaeroides and will shed light on the fundamental research of other bacteria that are hard to be directly edited by Cas9-sgRNA.

Several patient-derived tumor models emerged recently as robust preclinical drug-testing platforms. However, their potential to guide clinical therapy remained unclear. Here, we report a model called patient-derived tumorlike cell clusters (PTCs). PTCs result from the self-assembly and proliferation of primary epithelial, fibroblast, and immune cells, which structurally and functionally recapitulate original tumors. PTCs enabled us to accomplish personalized drug testing within 2 weeks after obtaining the tumor samples. The defined culture conditions and drug concentrations in the PTC model facilitate its clinical application in precision oncology. PTC tests of 59 patients with gastric, colorectal, or breast cancers revealed an overall accuracy of 93% in predicting their clinical outcomes. We implemented PTC to guide chemotherapy selection for a patient with mucinous rectal adenocarcinoma who experienced recurrence with metastases after conventional therapy. After three cycles of a nonconventional therapy identified by the PTC, the patient showed a positive response. These findings need to be validated in larger clinical trials, but they suggest that the PTC model could be prospectively implemented in clinical decision-making for therapy selection.

BACKGROUND:Although the involvement of individual microRNA and lncRNA in the regulation of p21 expression has largely been evidenced, less is known about the roles of functional interactions between miRNAs and lncRNAs in p21 expression. Our previous work demonstrated that miR-509- 3-5p could block cancer cell growth.METHODS:To gain an insight into the role of miR-509-3-5p in the regulation of p21 expression, we performed in silico prediction and showed that miR-509-3-5p might target the NONHSAT112228.2, a sense-overlapping lncRNA transcribed by a non-code gene overlapping with p21 gene. Mutation and luciferase report analysis suggested that miR-509-3-5p could target NONHSAT112228.2, thereby blocking its expression. Consistently, NONHSAT112228.2 expression was inversely correlated with both miR-509-3-5p and p21 expression in cancer cells. Ectopic expression of miR-509-3-5p and knockdown of NONHSAT112228.2 both promoted proliferation and migration of cancer cells.RESULTS:Interestingly, high-expression of NONHSAT112228.2 accompanied by low-expression of p21 was observed in lung cancer tissues and associated with lower overall survival.CONCLUSION:Taken together, our study found a new regulatory pathway of p21, in which MiR-509-3-5p functionally interacts with NONHSAT112228.2 to release p21 expression. MiR-509-3-5p- NONHSAT112228.2 regulatory axis can inhibit the proliferation and migration of lung cancer cells.

The currently synthetic methods of peptide heterodimer involve tedious synthesis and purification steps. An acid-labile traceless linker was prepared, which is highly compatible with the Fmoc strategy and could be used to prepare peptide heterodimer on resin. The linker could be cleaved concomitantly with peptide cleavage, and two model heterodimers were synthesized. The proposed synthesis procedure is simple, straightforward, and provides great convenience for preparing disulfide-linked peptide heterodimers.

LncRNAs represent a large class of noncoding RNA molecules that have important functions and play key roles in a variety of human diseases. There is an urgent need to develop bioinformatics tools as to gain insight into lncRNAs. This study developed a sequence-based bioinformatics method, LncDisease, to predict the lncRNA-disease associations based on the crosstalk between lncRNAs and miRNAs. Using LncDisease, we predicted the lncRNAs associated with breast cancer and hypertension. The breast-cancer-associated lncRNAs were studied in two breast tumor cell lines, MCF-7 and MDA-MB-231. The qRT-PCR results showed that 11 (91.7%) of the 12 predicted lncRNAs could be validated in both breast cancer cell lines. The hypertension-associated lncRNAs were further evaluated in human vascular smooth muscle cells (VSMCs) stimulated with angiotensin II (Ang II). The qRT-PCR results showed that 3 (75.0%) of the 4 predicted lncRNAs could be validated in Ang II-treated human VSMCs. In addition, we predicted 6 diseases associated with the lncRNA GAS5 and validated 4 (66.7%) of them by literature mining. These results greatly support the specificity and efficacy of LncDisease in the study of lncRNAs in human diseases. The LncDisease software is freely available on the Software Page: http://www.cuilab.cn/.

We developed a new efficient photolabile protecting group, 2-(2-nitrophenyl) propyl (Npp) that blocks the carboxyl group in peptide synthesis. The Npp group is quite compatible with the Fmoc-t-Bu strategy and can be removed rapidly and quantitatively by irradiation with UV light. Using this method, we prepared a head-to-tail cycloheptapeptide.

Long noncoding RNAs (lncRNAs) represent a big category of noncoding RNA molecules, and increasing studies have shown that they play important roles in various critical biological processes. They show a diversity of functions through diverse mechanisms, among which regulating RNA molecules is one of the most popular ones. Given the big number of lncRNAs, it becomes urgent and important to predict the RNA targets of lncRNAs in a large scale for the comprehensive understanding of lncRNA functions and action mechanisms. Although several methods have been developed to predict RNA-RNA interactions, none of them can be used to predict the RNA targets of lncRNAs in a large scale. Here we presented a tool, LncTar, which shows the ability to efficiently predict the RNA targets of lncRNAs in a large scale. To test the accuracy of LncTar, we applied it to 10 experimentally supported lncRNA-mRNA interactions. As a result, LncTar successfully predicted 8 (80%) of the 10 lncRNA-mRNA pairs, suggesting that LncTar has a reliable accuracy. Finally, we believe that LncTar could be an efficient tool for the fast identification of the RNA targets of lncRNAs. LncTar is freely available at http://www.cuilab.cn/lnctar.