Human HT-29, RKO, and SW480 CRC cells were cultured in a complete cell culture medium consisting of DMEM high glucose (Gibco, United States) supplemented with 10% vol. fetal bovine serum (Gibco, United States), 1% vol. GlutaMax (Gibco, United States), and 1% vol. antibiotic-antimycotic solution (Gibco, United States). The cells were incubated in a cell culture incubator (37°C, 5% CO₂). Subcultivation was performed every 2–3 days using trypsin-EDTA solution (PanEco, Russia). Cells were counted after trypan blue (Gibco, United States) staining using a Countess automated cell counter (Invitrogen, United States) according to the manufacturer’s protocol.

The organoid culture of CRC cells was established from resected metastatic tissue. Main clinical parameters of the three patients included in the study are summarized in Table 1. The study was approved by the local ethics committee.

To obtain primary organoid culture of CRC cells, resected metastatic tissue was used (Nikulin et al., 2020). The tissue sample was obtained during the examination of the surgically resected tissue block by a qualified pathologist who identified the resected tissue as a metastasis. Tissue was cut into small fragments and placed immediately into MACS tissue storage solution (Miltenyi Biotec, Germany). The sample was stored for several hours at 4°C. Then, the tissue fragments were transferred into a tube for tissue homogenization (gentleMACS C Tube, Miltenyi Biotec, Germany), and the enzyme cocktail from the Tumor Dissociation Kit Human (Miltenyi Biotec, Germany), which consisted of 2.2 ml of DMEM/F-12 culture medium (Thermo Fisher Scientific, United States), 100 μL of Enzyme H solution (Miltenyi Biotec, Germany), 50 μL of Enzyme R solution (Miltenyi Biotec, Germany), and 12.5 μL of Enzyme A solution (Miltenyi Biotec, Germany), was added to the same tube. Then, the tube was tightly closed with a lid and placed into a gentleMACS Octo Dissociator (Miltenyi Biotec, Germany). For tissue dissociation, the “37C_h_TDK_3” program was used. After the end of the program, the tube was removed from the dissociator. The resulting suspension was centrifuged at 300 g for 10 min. The supernatant was removed, and the pellet was resuspended in 10 ml of DPBS (Thermo Fisher Scientific, United States). Then, the suspension was recentrifuged with the same parameters, the supernatant was also removed, and the pellet was resuspended in DMEM/F-12 culture medium (Thermo Fisher Scientific, United States). Then, the tube with the suspension was placed on ice, and the suspension was mixed with Matrigel Growth Factor Reduced (GFR) Basement Membrane Matrix (Corning, United States) in the ratio 1:2. Then, 50 μL drops of the resulting suspension in the extracellular matrix were transferred into the wells of a 24-well culture plate (TPP, Switzerland) and placed into a cell culture incubator (37°C, 5% CO₂) for 20 min for solidification of the gel. Cell density in the resulting suspension in the extracellular matrix was 400,000 cells/ml. Then, 750 μL of complete cell culture medium was added to each well, and the plate was incubated in a cell culture incubator. The recipe of the complete cell culture medium for CRC organoids is based on previously published data with minor modifications (van de Wetering et al., 2015; Driehuis et al., 2020; Dekkers et al., 2021). The complete cell culture medium consisted of Advanced DMEM/F12 (Gibco, United States) supplemented with 1% vol. GlutaMax (Gibco, United States), 1% vol. antibiotic-antimycotic solution (Gibco, United States), 1% vol. HEPES (Gibco, United States), 2% vol. B27 (Gibco, United States), 1.25 mM n-Acetyl Cysteine (Sigma, United States), 10 mM Nicotinamide (Sigma, United States), 250 ng/ ml R-spondin 1 (PeproTech, United States), 100 ng/ ml Noggin (PeproTech, United States), 50 ng/ ml human EGF (Gibco, United States), 10 nM Gastrin I (Sigma, United States), 500 nM A83-01 (STEMCELL Technologies, Canada), 1 uM SB202190 (Tocris Bioscience, United Kingdom), 10 nM Prostaglandine E2 (Sigma, United States), and 5 uM Y-27632 (STEMCELL Technologies, Canada). Cell culture medium was replaced every 48 h. Cells were inspected visually by an inverted Primo Vert microscope (Carl Zeiss, Germany). Organoids were subcultured (1:5 dilution) every 2 weeks with the help of TrypLE Express (Thermo Fisher Scientific, United States).

Fragments of the original tumor tissue were fixed in 10% neutral buffered formalin (overnight at room temperature) and embedded in paraffin. Formalin-fixed samples of tumor organoids were covered with Histogel (Thermo Fisher Scientific, United States) and then embedded into paraffin. Serial sections with a thickness of 4 μm were cut and then were routinely stained with hematoxylin-eosin and then examined by light microscopy.

Next-generation sequencing of the DNA isolated from the tumor tissue and organoids was carried out with the Oncomine Comprehensive Assay V3 (Thermo Fisher Scientific, United States) based on the Ion Torrent S5 System (Thermo Fisher Scientific, United States). Snap-frozen tumor tissue and organoids were used for isolation of DNA. The alignment was carried out on the basis of the GRCh37 genomic assembly. Single nucleotide variants (SNV) and small insertions and deletions (indel) as well as larger genome rearrangements were identified by Atlas Oncology Diagnostics (Ivanov et al., 2019).

To detect more pronounced changes in mRNA levels, organoids and cell lines were treated with 9-ING-41 for 24 h (Duffy et al., 2014). Then, cells were lysed with the QIAzol Lysis Reagent (Qiagen, Germany). The lysates were stored at −80°C before RNA isolation. RNA isolation was performed using miRNeasy Micro Kit (Qiagen, Germany) according to the manufacturer’s protocol. Nanodrop ND-1000 (Thermo Fisher Scientific, United States) was used to assess quantity and purity of the extracted RNA. Total RNA samples were also QC-checked using an Agilent 2100 Bioanalyzer (Agilent Technologies, United States). For each group, three independently obtained samples of RNA were used.

Libraries for mRNA sequencing were prepared from total RNA samples using an Illumina Stranded mRNA Library Prep Kit (Illumina, United States). Each sample was sequenced on the NextSeq 550 (Illumina, United States) to generate paired-end, 75-nucleotide reads.

Real-time PCR was used to assess changes in the expression of selected individual genes. Reverse transcription of RNA was performed using the MMLV RT kit (Evrogen, Russia) according to the manufacturer’s protocol. The obtained cDNA samples were stored at −20°C. qPCRmix-HS SYBR (Evrogen, Russia) was used for RT-PCR performed with DTprime detecting amplifier (DNA Technology).

The oligonucleotide primers used for RT-PCR were designed based on the mRNA sequences of the studied genes from the UCSC Genome Browser database (Kent et al., 2002). Primer selection was performed using Primer-BLAST software (Ye et al., 2012). ACTB and GAPDH were selected as reference genes. The sequences of the primers used for RT-PCR are presented in Table 2. The evaluation of the differences in the expression of the selected genes resulting from the addition of 9-ING-41 in comparison with the control cells was carried out using the software REST 2009 v.2.0.13 (Pfaffl et al., 2002; Vandesompele et al., 2002).

The quality of FASTQ files was assessed with FastQC v0.11.9 (Babraham Bioinformatics, United Kingdom) and multiQC v1.9 (Ewels et al., 2016). The adapters were trimmed with fastp 0.21.1 (Chen et al., 2018). The trimmed mRNA-seq reads were mapped on the reference human genome GENCODE release 37 (GENCODE GRCh38. primary assembly) with STAR 2.7.7a (Dobin et al., 2013). GENCODE release 37 genome annotation (gencode.v37. primary assembly. annotation) (Frankish et al., 2019) was used to generate the count matrix with the featureCount tool from ssubread-2.0.1 aligner (Liao et al., 2013, 2014).

Differential expression analysis was conducted using DESeq2 v1.28.1 (Love et al., 2014). False discovery rates (FDRs) were calculated by the Benjamini–Hochberg procedure. To assess the statistical significance of differences in gene expression, FDR p-values with threshold level of .05 were used. To construct heat maps of gene expression, regularized-logarithm transformation of counts was used (Love et al., 2014). Only differentially expressed genes (FDR p-values < .05) were included in the heat maps.

Gene set enrichment analysis was performed with GSEA 4.1.0 (Mootha et al., 2003; Subramanian et al., 2005). The Hallmark (Liberzon et al., 2015), Canonical pathways (includes gene sets from BIOCARTA (Nishimura, 2001), KEGG (Kanehisa, 2000), PID (Schaefer et al., 2009), REACTOME (Jassal et al., 2019) and WikiPathways (Martens et al., 2021) pathway databases), GTRD subset of TFT (Kolmykov et al., 2021), miRDB subset of MIR (Chen and Wang, 2020), and Oncogenic signature gene sets were included in the analysis (Liberzon et al., 2011). To assess the statistical significance of gene set enrichment, FDR p-values with a threshold level of .05 were used.

HT-29, RKO, and SW480 cells were seeded into 96-well plates (TPP, Switzerland) in 100 ul of complete cell culture medium (5000 per well). Organoids were diluted in Matrigel GFR Basement Membrane Matrix (Corning, United States) and seeded into 96-well plates (TPP, Switzerland) (50 organoids per well). After solidification of the gel, 100 ul of complete cell culture medium was added into each well.

After 24 h, the cell culture medium was replaced with medium containing single SoC drugs and SoC drug combinations with or without 9-ING-41. Clinically relevant concentrations were used in the assay: 25 uM for 5-FU (Sigma, United States) (Larsson et al., 1996), 10 uM for Oxaliplatin (Medac, Germany) (Graham et al., 2000), and 2 uM for 9-ING-41 (Ugolkov et al., 2016; Kuroki et al., 2019). 9-ING-41 was synthesized and tested according to a previously published procedure (Gaisina et al., 2009). Stock solutions of 5-FU and 9-ING-41 were prepared in DMSO; stock solution of Oxaliplatin was prepared in water (Hall et al., 2014). The treatments were compared with vehicle controls containing the same quantity of DMSO and water.

Then cells were incubated for 3 h in a cell culture incubator (37°C, 5% CO₂), and the medium was replaced with fresh complete cell culture medium. Then, plates were incubated in a cell culture incubator (37°C, 5% CO₂) for 72 h. The relative number of viable cells was measured with the MTS assay CellTiter 96 Aqueous One Solution Cell Proliferation Assay kit (Promega, United States) according to the manufacturer’s instructions (Steele et al., 2019). Growth rate of cancer cells was calculated as described previously (Hafner et al., 2016).

Each experiment was performed three times for cell lines and five times for organoids; three technical replicates were used in each experiment. Two-way ANOVA with Tukey post hoc test was used to assess changes in the growth rate of cancer cells in the drug tests. The first factor was SoC treatment with the levels corresponding to different SoC drugs and combinations. The second factor was 9-ING-41 (presence or absence of 9-ING-41). The differences were considered statistically significant if adjusted p-values were less than .05.

Patient-derived tumor organoids (PD-TOs) were generated starting from digested tissue, embedded in 50 μL of Matrigel, and cultured for a maximum of 3 weeks without passaging. After subculturing, we observed extensive cell growth starting from the second day of the seeding (Figure 1).

To determine whether the generated organoids consist of CRC cells rather than normal epithelial cells, we performed H&E histologic analysis of primary tumor organoids. An experienced pathologist compared cell morphology in organoids to the primary tumors and confirmed that all generated organoids cultures consist of malignant cells (Figure 2).

The analysis of mutations in tumor tissue and tumor organoids (Figure 3, Supplementary Table S1) revealed that the initial tissue from liver metastasis of Patient 1 contained only one SNV in the POLE gene (p.F990S). This variant was not found in the Catalogue of Somatic Mutations in Cancer and most probably represents a germline mutation (Tate et al., 2019). In the corresponding tumor organoids, in addition to the same SNV in the POLE gene, several other point mutations were identified: KRAS (p.G12D), TP53 (p.V173A), and NOTCH2 (p.R2051Q). Moreover, two large genome rearrangements were also detected; the first one involved BRAF and SND1 genes, and the second one involved FGFR1 and WHSC1L1 genes.

Lung metastasis tissue from Patient 2 contained two different mutations in the TP53 gene (p.C135Y and p. C135S) and single mutations in NOTCH2 (p.A3F) and RNF43 (p.R117S) genes. These mutations were conserved in tumor organoids. No large genome rearrangements were found in tumor tissue as well as in tumor organoids from Patient 2.

Initial metastatic tumor tissue from Patient 3 contained the following mutations: KRAS (p.G12C), TP53 (p.P177R), and KIT (p.A621T). The same mutations were found in the corresponding tumor organoids. Neither initial tumor tissue nor tumor organoids from Patient 3 contained large genome rearrangements.

Analysis of the sensitivity of CRC cell lines to the SoC drugs and 9-ING-41 demonstrated various types of response (Figure 4). The growth inhibitory effect of the single SoC drugs and their combination was statistically significant (p < .05) for all tested cell lines and ranged from 12% to 64%. On the other hand, response to 9-ING-41 was more heterogenous. For example, HT-29 cells were resistant to the transient inhibition of GSK-3β by 9-ING-41 (Figure 4A). Moreover, 9-ING-41 did not improve the results of the SoC drugs (p > .05) in this case. In contrast, RKO cells (Figure 4B) were sensitive to 9-ING-41 (p < .05), and it significantly enhanced the growth inhibitory effect of 5-FU (p < .05), oxaliplatin (p < .05), and their combination (p < .05). SW480 cells (Figure 4C) were resistant to pure 9-ING-41; however, the growth inhibitory effect of the combination of 5-FU and oxaliplatin was more pronounced in the presence of 9-ING-41 (p < .05).

Overall, all tested patient-derived tumor organoids were more sensitive to 9-ING-41. For Patient 1, analysis of the results of the drug tests (Figure 5A) revealed that clinically relevant concentrations (Larsson et al., 1996; Graham et al., 2000) of neither 5-FU (p = .99) nor Oxaliplatin (p = .17) significantly inhibited growth of PD-TOs. The combination of these two drugs was also ineffective (p = .1). In contrast, 9-ING-41 markedly reduced the growth rate of the CRC organoids from Patient 1 by 44%–62% both alone (p < .05) and in combination with the tested SoC drugs (p < .05). Moreover, addition of 9-ING-41 to the tested single SoC drugs as well as to their combination always led to better results in comparison with the corresponding treatment without 9-ING-41 (reduction of the growth rate by 38%–43%, p < .05). However, the magnitude of the effect of the combinations of 9-ING-41 with the SoC drugs did not differ statistically significant from pure 9-ING-41, suggesting that the main effect in this case is produced by 9-ING-41 rather than SoC drugs.

For Patient 2, it was shown (Figure 5B) that both 5-FU and Oxaliplatin as well as their combination almost completely stopped the growth of cancer cells (p < .05). Addition of 9-ING-41 to these treatment variants did not change significantly the growth rate (p = 1 for 5-FU and Oxaliplatin, p = .99 for 5-FU + Oxaliplatin). Interestingly, in this particular case, single 9-ING-41 also significantly reduced the growth rate (p < .05), and its effect was indistinguishable from the SoC treatment (p = .66 for 5-FU, p = .98 for Oxaliplatin, and p = .89 for 5-FU + Oxaliplatin) as well as from the combination of SoC treatment with 9-ING-41 (p = .54 for 5-FU, p = .98 for Oxaliplatin, and p = .42 for 5-FU + Oxaliplatin).

For Patient 3, the drug test revealed (Figure 5C) that both 5-FU (p < .05) and Oxaliplatin (p < .05) as well as their combination (p < .05) significantly reduced the growth rate of colorectal tumor organoids by 28%–49%. 9-ING-41 alone, in this case, was also active and decreased the growth rate by 32% (p < .05). Moreover, the effect of pure 9-ING-41 was not significantly different from the SoC treatment variants (p = 1 for 5-FU and Oxaliplatin and p = .35 for 5-FU + Oxaliplatin). Interestingly, addition of 9-ING-41 to the single SoC drugs 5-FU and Oxaliplatin improved the effect of the treatment by around 30% (p < .05 and p = .05 respectively). In both cases, the growth inhibitory effect of the combinations containing 9-ING-41 was significantly better than the effect of pure 9-ING-41 (p < .05 for both 5-FU and Oxaliplatin). All these data suggest the presence of the additional therapeutic effect between the single SoC drugs and 9-ING-41. In the case of combination of 5-FU and Oxaliplatin, the benefit from 9-ING-41 (around 20% reduction in the growth rate) did not reach statistical significance (p = .14), but the effect of the combination was significantly better than the effect of 9-ING-41 alone (p < .05).

Overall, our data demonstrate that the response of colorectal cell lines to transient action of 9-ING-41 can vary. In some cases, it can be active alone, and sometimes it can significantly enhance the growth inhibitory effect of the SoC drugs. On the other hand, in all analyzed samples of tumor organoids, 9-ING-41 was active and decreased the growth rate of CRC cells. Its efficiency was either significantly higher than one of the SoC drugs (Patient 1) or comparable to it (Patients 2 and 3). Moreover, in case of intermediate (Patient 3) or low (Patient 1) sensitivity to the SoC drugs, addition of 9-ING-41 can markedly improve the results of the standard treatment.

To elucidate molecular mechanisms underlying the ability of 9-ING-41 to overcome chemotherapy resistance in CRC cells, we carried out a transcriptome analysis of the most resistant organoids derived from Patient 1.

Overall, transcriptomic analysis revealed (Supplementary Table S2) that, after treatment with 9-ING-41 for 24 h, 325 genes significantly changed their expression (FC > 1.5, FDR p-value < .05): 155 were upregulated, and 170 were downregulated. Further GSEA showed that 280 gene sets were significantly upregulated, and 118 gene sets were significantly downregulated after treatment with 9-ING-41 (Supplementary Table S3).

The top enriched downregulated gene set was HALLMARK E2F TARGETS (FDR p < .001), containing the genes encoding cell cycle–related targets of E2F transcription factors (Figures 6A,C). Top downregulated genes from this gene set were TUBB (FC = −2.4, FDR p < .001), SPC24 (FC = −2.0, FDR p < .001), and AURKB (FC = −1.9, FDR p < .001). E2F together with CDK and RB proteins form the key transcription machinery for cell cycle progression (Kent and Leone, 2019). Interestingly, a lot of other gene sets related to E2F were also significantly downregulated. This list includes E2F3 UP.V1 UP (FDR p = .008), PID E2F PATHWAY (FDR p = .01), reactome transcription of e2f targets under negative control by dream complex (FDR p = .02), reactome transcription of E2F targets under negative control BY P107 RBL1 AND P130 RBL2 in complex with HDAC1 (FDR p = .02), and E2F1 UP.V1 UP (FDR p = .03). Moreover, the gene set WP RETINOBLASTOMA GENE IN CANCER (FDR p < 0.001) was among the top five downregulated ones. Also worth noting is that the gene sets produced previously in the experiments on knockout of RB in mice keratinocytes (Lara et al., 2008) were also significantly downregulated: RB DN. V1 UP (FDR p = .001), RB P107 DN. V1 UP (FDR p < .001), RB P130 DN. V1 UP (FDR p = .02).

In addition to the CDK-RB-E2F axis, a lot of other gene sets, related to the cell cycle were enriched in control cells in comparison to the treated cells, indicating global suppression of cell cycle progression by 9-ING-41 (Table 3), including hallmark G2M checkpoint (Figures 6B,D), reactome G1 s specific transcription, and reactome mitotic prometaphase. Interestingly, a number of other gene sets connected to DNA repair and telomere maintenance were also suppressed after treatment with 9-ING-41 (Figure 7; Table 4).

The top enriched upregulated gene set was STK33 SKM UP (FDR p = 0.002), containing the genes upregulated in SKM-1 acute myeloid leukemia (AML) cells after knockdown of STK33. Another two gene sets related to STK33, named STK33 NOMO UP (FDR p = .001, contains the genes upregulated in NOMO-1 AML cells after knockdown of STK33) and STK33 UP (FDR p = .001, combines two previously mentioned gene sets) were also in the top five list of the enriched upregulated gene sets (Figures 8A,C). The most significantly regulated genes from the gene set STK33 UP were MMP1 (FC = 2.4, FDR p < .001), H2BC8 (FC = 2.3, FDR p < .001) and CYBRD1 (FC = 7.2, FDR p = .048). Interestingly, the STK33 DN gene set, which consisted of the genes that were downregulated in NOMO-1 and SKM-1 cells after knockdown of STK33, was also downregulated after treatment with 9-ING-41 (Figures 8B,D), but the changes were insignificant after correction for multiple comparisons (p < .001, FDR p = .33). STK33 is a gene located in human chromosomal region 11p15 and codes a serine/threonine kinase (Mujica et al., 2001). It is shown that knockdown of STK33 leads to a decrease in viability of KRAS mutant cancer cells (Scholl et al., 2009). Thus, our results suggest that action of 9-ING-41 can have similarities with suppression of STK33.

To verify the results of the RNA-seq, we performed RT-PCR for selected genes from the enriched gene sets (Figure 9). We chose TUBB gene (RNA-seq FC = −2.4, FDR p < .05) from the HALLMARK E2F TARGETS gene set, UBE2C gene (RNA-seq FC = −1.7, FDR p < .05) from the HALLMARK G2M CHECKPOINT gene set, CDK1 gene (RNA-seq FC = −1.5, FDR p < 0.05) from the WP DNA IRDAMAGE AND CELLULAR RESPONSE VIA ATR gene set and MMP1 gene (RNA-seq FC = 2.4, FDR p < .05) from the STK33 UP gene set. Three of these genes are related to the cell cycle. The TUBB gene encodes β-tubulin protein, which is one of the major components of mitotic spindle (Parker et al., 2014). The UBE2C gene encodes one of the members of the anaphase-promoting complex, which is responsible for degradation of several target proteins along cell cycle progression (Nicolau-Neto et al., 2018). CDK1 (cyclin-depended kinase 1) is one of the key parts of the cell cycle progression machinery (Kent and Leone, 2019), and it also participates in DNA repair (Johnson and Shapiro, 2010). MMP1 is a matrix metalloproteinase that primarily breaks down native collagens and gelatin (Overall, 2002).

RT-PCR analysis of the organoids from Patient 1 confirmed the findings of the RNA-seq for all tested genes: TUBB (RT-PCR FC = −2.3, p < .05), UBE2C (RT-PCR FC = −1.3, p < .05), CDK1 gene (RT-PCR FC = −2.3, p < .05), and MMP1 gene (RT-PCR FC = 2.6, p < .05).

Interestingly, almost the same changes were observed for the HT-29 and RKO cell lines. The expression of the MMP1 gene was too low in the cell lines to be measured with RT-PCR (the signal was lower than the threshold value after 40 cycles). However, the expression levels of the other genes were measured and demonstrated changes in the same direction. In HT-29 cells after the treatment with 9-ING-41, the expression of the TUBB gene decreased 2.6 times (p < .05), of the UBE2C gene 2.2 times (p < .05), and of the CDK1 gene 1.8 times (p < .05). For the RKO cells, the changes were even more pronounced: TUBB (RT-PCR FC = −3.3, p < .05), UBE2C (RT-PCR FC = -2.1, p < .05), and CDK1 gene (RT-PCR FC = −4.7, p < .05). Thus, our data demonstrate that the changes in mRNA profile after the treatment with 9-ING-41 are not specific for Patient 1 organoids and can be observed in other models of colorectal cancer.